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Simple explanations of Artificial Intelligence, Machine Learning, and Deep Learning and how they’re all different. Plus, how AI and IoT are inextricably connected.

We’re all familiar with the term “Artificial Intelligence.” After all, it’s been a popular focus in movies such as The Terminator, The Matrix, and Ex Machina (a personal favorite of mine). But you may have recently been hearing about other terms like “Machine Learning” and “Deep Learning,” sometimes used interchangeably with artificial intelligence. As a result, the difference between artificial intelligence, machine learning, and deep learning can be very unclear.

I’ll begin by giving a quick explanation of what Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) actually mean and how they’re different. Then, I’ll share how AI and the Internet of Things are inextricably intertwined, with several technological advances all converging at once to set the foundation for an AI and IoT explosion.

So what’s the difference between AI, ML, and DL?

First coined in 1956 by John McCarthy, AI involves machines that can perform tasks that are characteristic of human intelligence. While this is rather general, it includes things like planning, understanding language, recognizing objects and sounds, learning, and problem solving.

We can put AI in two categories, general and narrow. General AI would have all of the characteristics of human intelligence, including the capacities mentioned above. Narrow AI exhibits some facet(s) of human intelligence, and can do that facet extremely well, but is lacking in other areas. A machine that’s great at recognizing images, but nothing else, would be an example of narrow AI.

At its core, machine learning is simply a way of achieving AI.

Arthur Samuel coined the phrase not too long after AI, in 1959, defining it as, “the ability to learn without being explicitly programmed.” You see, you can get AI without using machine learning, but this would require building millions of lines of codes with complex rules and decision-trees.

So instead of hard coding software routines with specific instructions to accomplish a particular task, machine learning is a way of “training” an algorithm so that it can learnhow. “Training” involves feeding huge amounts of data to the algorithm and allowing the algorithm to adjust itself and improve.

To give an example, machine learning has been used to make drastic improvements to computer vision (the ability of a machine to recognize an object in an image or video). You gather hundreds of thousands or even millions of pictures and then have humans tag them. For example, the humans might tag pictures that have a cat in them versus those that do not. Then, the algorithm tries to build a model that can accurately tag a picture as containing a cat or not as well as a human. Once the accuracy level is high enough, the machine has now “learned” what a cat looks like.

Deep learning is one of many approaches to machine learning. Other approaches include decision tree learning, inductive logic programming, clustering, reinforcement learning, and Bayesian networks, among others.

Deep learning was inspired by the structure and function of the brain, namely the interconnecting of many neurons. Artificial Neural Networks (ANNs) are algorithms that mimic the biological structure of the brain.

In ANNs, there are “neurons” which have discrete layers and connections to other “neurons”. Each layer picks out a specific feature to learn, such as curves/edges in image recognition. It’s this layering that gives deep learning its name, depth is created by using multiple layers as opposed to a single layer.

AI and IoT are Inextricably Intertwined

I think of the relationship between AI and IoT much like the relationship between the human brain and body.

Our bodies collect sensory input such as sight, sound, and touch. Our brains take that data and makes sense of it, turning light into recognizable objects and turning sounds into understandable speech. Our brains then make decisions, sending signals back out to the body to command movements like picking up an object or speaking.

All of the connected sensors that make up the Internet of Things are like our bodies, they provide the raw data of what’s going on in the world. Artificial intelligence is like our brain, making sense of that data and deciding what actions to perform. And the connected devices of IoT are again like our bodies, carrying out physical actions or communicating to others.

Unleashing Each Other’s Potential

The value and the promises of both AI and IoT are being realized because of the other.

Machine learning and deep learning have led to huge leaps for AI in recent years. As mentioned above, machine learning and deep learning require massive amounts of data to work, and this data is being collected by the billions of sensors that are continuing to come online in the Internet of Things. IoT makes better AI.

Improving AI will also drive adoption of the Internet of Things, creating a virtuous cycle in which both areas will accelerate drastically. That’s because AI makes IoT useful.

On the industrial side, AI can be applied to predict when machines will need maintenance or analyze manufacturing processes to make big efficiency gains, saving millions of dollars.

On the consumer side, rather than having to adapt to technology, technology can adapt to us. Instead of clicking, typing, and searching, we can simply ask a machine for what we need. We might ask for information like the weather or for an action like preparing the house for bedtime (turning down the thermostat, locking the doors, turning off the lights, etc.).

Converging Technological Advancements Have Made this Possible

Quickly improving battery technology means those sensors can last for years without needing to be connected to a power source.

Wireless connectivity, driven by the advent of smartphones, means that data can be sent in high volume at cheap rates, allowing all those sensors to send data to the cloud.

And the birth of the cloud has allowed for virtually unlimited storage of that data and virtually infinite computational ability to process it.

Of course, there are one or two concerns about the impact of AI on our society and our future. But as advancements and adoption of both AI and IoT continue to accelerate, one thing is certain; the impact is going to be profound.

It’s healthy to be skeptical of new ideas, but let’s take a look at the philosophy that might be holding back the biggest advancement in technology in a century.

In about exactly 13 years (target as set by NASA) or rather 7 years (as set by Elon Musk’s Space-X) from now, we humans are going to set foot on Mars and become a truly space-faring race.

We live in pretty exciting times riding on a threshold of Continuous Imagination empowering Continuous Innovation. Every product in every domain is undergoing a sea change, adding new features, releasing them faster than their competitors, adapting to incremental rate of technological substitution. But most of these new feature improvements and product launches are not guided by new requirements from customers. In the face of stiff competition that gets stiffer by the day, evolution and adaptation is the only natural process of survival and winning. As Charles Darwin would put it, it’s, “Survival of the fittest.”

But as history suggests, there are and there always will be skeptics among us who will doubt every action that deviates from convention – like those who doubt climate change, the need to explore the unexplored, and the need to change.

A human mind exposed to scientific education exhibits skepticism and pragmatism over dogmatism and largely remains technology-agonistic. It validates everything agnostically with knowledge and reasoning before accepting new ideas. But human progress always comes from philosophical insights — imaginations that led to the discovery or invention of new things. Technological progress has only turned science fiction (read: philosophy) into scientific facts.

With the above premises in mind, in this article, we intend to explore the realm of IoT, its implications on our lives, and our own limitations in foreseeing the imminent future as companies and customers.

We Understand the Internet, but not IoT

IoT, the Internet of Things (or Objects), denote the entire network of Internet-connected devices – vehicles, home and office appliances, and machinery equipment embedded with electronics, software, sensors, actuators, and the wired/Wi-Fi and RFID network connectivity that enable these objects to connect and exchange data. The benefits of this new ubiquitous connectivity will be reaped by everyone, and we will, for the first time, be able to hear and feel the heartbeat of the Earth.

For example, as cows, pigs, water pipes, people, and even shoes, trees, and animals become connected to IoT, farmers will have greater control over diseases affecting milk and meat production through the availability of real-time data and analytics. It is estimated that, on average, each connected cow will generate around 200 MB of data every month.

According to Cisco, back in 2003, the penetration of the Internet and connected devices per person was really low — but that grew at an exponential rate, doubling after every 5.32 years. That’s similar to the properties of Moore’s Law. Between 2008 and 2009, with the advent of smartphones, these figures rocketed, and it was predicted that 50 billion connected devices shall be in use by the year 2020. Thus, IoT was born and is in its adolescent phase already.

Today, IoT is well underway, as seen in initiatives such as Cisco’s Planetary Skin, smart grid, and intelligent vehicles, HP’s central nervous system for the earth (CeNSE), and smart dust, have the potential to add millions — even billions — of sensors to the Internet.

But just like as in during the social media explosion, the new age of IoT, connected devices, connected machines, connected cars, connected patients, connected consumers, and connected networks of Things we will need new age collaboration tools, new software, new database technologies, and infrastructure to accommodate, store and analyze huge amounts of data that will be generated — like the host of emerging technologies including graph databases, Big Data, microservices, and so on.

But that’s not all.

The Internet of Things will also require IOE – Integration of Everything — for meaningful interaction between devices and provides.

But as Kai Wähner of TIBCO discusses in his presentation “Microservices: Death of the Enterprise Service Bus,” microservices and API-led connectivity are ideally matched to meet integration challenges in the foreseeable future. MuleSoft’s “Anypoint Platform for APIs” backed by Cisco, Bosch’s “IoT platform,” or the upcoming API management suite from Kovair is a pointer to all this and shall empower the IoT revolution.

The explosion of connected devices — each requiring a specific IP address — already exhausted what was available in 2010 under IPv4 and required IPv6’s implementation immediately. In addition to opening up more IP addresses, IPv6 will also suffice for intra-planetary communication for a much longer period. Governments and the World Wide Web Consortium have remained laggards and skeptical with IPv6 implementation and allowed the exhaustion of IP addresses.

But it hasn’t been just governments. Bureaucratic and large, technology-driven organizations like Amazon, Google, and Facebook can remain skeptics under disguise and continue to block movements like Net Neutrality/ ZeroNet, Blockchain technology, IPFS (Inter Planetary File Sharing protocol), the overly cumbersome HTTP as they fear their monopolies will be challenged.

Conclusion

We humans, engaged in different capacities as company executives, consumers, government officials, or technology evangelists, are facing the debate of skepticism vs. futurism and will continue to doubt IoT — embracing it only incrementally until we see true, widespread benefits from it.

And we can see how our skepticism has worked against recognition and advancement.

After remaining skeptical for 120 years, the IEEE finally recognized the pioneering work done in by the Indian Physicist J.C. Bose during colonial rule and conferred on him the designation of the “Father of Telecommunication”. The mm wavelength frequency that he invented in his experiment in 1895 in Kolkata is the foundation of 5G (Wi-Fi Mobile network) that scientists and technologists across the world are now trying to reinvent that will provide the backbone for IoT.

Finally, we leave it to the reader’s imagination about the not-so-distant future, when all the connected devices in IoT begin to pass the Turing Test.

From home appliances to health applications and security solutions, everything we use at home – and outside of it, is getting connected to the Internet, becoming the Internet of Things (IoT). Think about how many connected devices you have at home: tablets, laptops, e-readers, fitness devices, smart TVs – how about your thermostat, light bulbs, refrigerator and security system? Our home has effectively become a connected home, with an average of 12 things connecting to our home Wi-Fi network, transmitting data and delivering added value. But as connected home appliances continue to grow, so too will the cybersecurity risks.

Consumers have been fast to adopt IoT devices on the promise that they can improve our lifestyles. These things track and optimize our energy consumption, facilitate our daily tasks, improve our health and wellness, keep us secure and empower us with the freedom and data to do other things better. But from a security point of view, this unregulated, insecure and fragmented market represents a clear and present danger to individuals and society as a whole, from the cyber to the physical realm.

To protect connected homes, a multi-faceted approach is recommended, combining a firewall blocking mechanism with machine learning and artificial intelligence to detect network anomalies. Millions of IoT devices are already compromised and we recommend communication service providers (CSPs) to initiate deployment of cybersecurity solutions today in parallel to their own R&D plans. By providing cybersecurity solutions through partnerships, they can begin to protect their vulnerable clients today and establish a market leadership position.

Cyber-threats

The declining costs to manufacture chips that can store and transmit data through a network connection have enabled thousands of organizations and startups to bring IoT products to market. But the current lack of standards and security certifications, coupled with fierce market competition to deliver affordable IoT products, have made cybersecurity an expense that manufacturers prefer others to deal with.

The lack of experience and incentives in the IoT supply chain to provide secure devices has created a tremendously vulnerable IoT landscape. In fact, according to recent findings by Symantec, IoT devices can become compromised within two minutes of connecting to the Internet1. Legislation has been too slow to deal with the current threat, and although there are public initiatives to drive cyber awareness among consumers, we do not expect any tangible changes soon.

There are many attack vectors and vulnerabilities to worry about in the Connected Home. From poor design decisions and hard-coded passwords to coding flaws, everything with an IP address is a potential backdoor to cyber crimes. Traditional cybersecurity companies reacted slowly and failed to provide defense solutions to the expanding universe of IoT devices. However, novel approaches with Artificial Intelligence and Machine Learning – such as analyzing and understanding network behaviors to detect anomalies, are now available to defend against these new threats.

With all its challenges and opportunities, consumer IoT is destined to disrupt long-established industries, making it a space one cannot afford to ignore. One such long-established industry is precisely the one powering the revolution: the CSPs providing the broadband. By and large, telecommunication companies have failed to monetize the data running through their home gateways, missing out in big opportunities. We believe that the connected home, especially cybersecurity, is a low-hanging fruit that communication service providers can and should pick before it’s too late.

Home security and safety-related appliances are top revenue drivers in the connected home landscape, and telecom companies are well positioned to enter this market and rebrand themselves as innovative and secure companies interested in the well-being and privacy of their customers. By leveraging their existing assets, such as the home router, telecoms can provide holistic solutions that include cybersecurity, data management and customer support – giving them a unique advantage over their competitors. Consumers would much rather trust their CSPs to continue managing their data than giving it away to foreign or unknown companies. It is time for Internet Service Providers to reclaim their value as a Service Provider, else they risk missing out in this revolution as broadband continues to become commoditized.

Stories of hacked IoT devices abound, a quick search online will lead you to scary stories, from spying Barbie dolls2, to TV sets monitoring you3 and creeps accessing baby cameras4. Most ironic and worrying of all are the security threats inherent in best-selling security systems, which can allow hackers to control the whole system, due to lack of encryption and sufficient cybersecurity standards5.

The cyber and physical risks intensify the more devices we connect: The volume of granular data that all these connected things generate when combined can provide a very detailed profile of the user, which can be used for identity theft and blackmail.

Once an unprotected IoT device gets hacked, a skilled hacker can proceed to infect other devices in the network via “lateral movement”. By jumping from one device to another, a hacker can gain complete control of a connected home. Because this threat comes from within the network, it is important to have a security solution that provides network visibility, creates device profiles and detects anomalies through machine learning and artificial intelligence.

There have been enough stories in the news for the average consumer to be aware of cyber threats, they know security is important and that they don’t have it, but they lack the resources to properly protect themselves. IoT manufacturers should be held accountable to prioritize security, but until that happens, the responsibility and opportunity falls on CSPs to protect the consumers.

Structural Risks

What makes the IoT ecosystem a potentially deadly cyber threat is the combined computing and networking power of thousands of devices which, when operated together as a botnet, can execute massive Distributed Denial of Service (DDoS) attacks and shut down large swaths of the Internet through a fire hose of junk traffic. The IoT ecosystem represents a totally different level of complexity and scale in terms of security and privacy.

In October 2016, we got a taste of this structural risk when the infamous Mirai botnet attacked the DNS company Dyn with the biggest DDoS attack ever reported: more than 1 terabit per second (Tbps) flooded the service, temporarily blocking access to Netflix, Twitter, Amazon, PayPal, SoundCloud, New York Times and others. The Mirai botnet used enslaved IoT devices -nearly 150,000 hacked cameras, routers and smart appliances, to inadvertently do its criminal bidding, and most of the infected devices remain out there, with their users oblivious to the fact.

The way Mirai malware spreads and attacks is well known: it scans the web for open Telnet and SSH ports, browsing for vulnerable devices using factory default or hard-coded usernames and passwords, then uses an encrypted tunnel to communicate between the devices and command and control (C&C) servers that send instructions to them. Since Mirai uses encrypted traffic, it prevents security researchers from monitoring the command and data traffic.

The source code for Mirai was posted soon after on the Hackforums site6, enabling other criminals to create their own strains of the malware. It is not necessary to have an “army” of thousands of infected devices to cause harm. Mini-DDoS botnets, with hundreds of compromised nodes, are sufficient to cause temporary structural damage and reduce the chances of getting caught -expect more of these attacks in the future.

Capturing vulnerable devices to turn them into botnets has become a cyber crime gold rush, with an estimated 4000 vulnerable IoT devices becoming active each day7, and criminals selling and renting botnets in the dark net at competitive prices to cause harm. Although simple to understand, this sort of malware is hard to detect because it does not generally affect device performance, so the average user cannot know if their device is part of a botnet – and even if they did, it’s often difficult to interact with IoT devices without a user interface.

Stakeholders should take proactive steps that can prevent future incidents by addressing the lack of security-by-design in the IoT landscape. The Mirai malware was a warning shot, and organizations must be prepared for larger and potentially more devastating attacks. Because of market failures at play, regulation seems like the only way forward to incentivize device manufacturers to implement security in their design, but doing so could stifle innovation and prove disastrous to the ecosystem. It is because of this delicate balance that we believe service providers are perfectly positioned to seize this problem as an opportunity to become market leaders in the emerging field of IoT cybersecurity.

Looking Forward

The frequency of cyber threats is increasing as the IoT landscape continues to expand. Gartner predicts that by 2020, addressing compromises in IoT security will have increased security costs to 20% of annual security budgets, from less than one percent in 20158. The threats to consumers and society are numerous, but joint cybersecurity and cyber-hygiene efforts by manufacturers, legislators, service providers and end users, will mitigate the inherent risks discussed in this paper.

Until that happens, service providers are uniquely positioned and encouraged to begin offering cybersecurity services to their consumers through their home gateways: the main door of the home network. Communication Service Providers that provide home network security and management solutions today can become the preferred brand for Smart Home solutions and appliances, leading IoT market adoption while preventing the cyber risks associated with it.

Netonomy has developed a solution that is available today for service providers interested in providing a layer of security to their consumers and become a trusted market leader in the emerging IoT landscape. Because it is cloud-based, this solution can be instantly deployed across thousands of routers at a low cost and bring immediate peace of mind to consumers.

Netonomy’s Solution: Netonomy provides a simple, reliable and secure network for the connected home. Through a minimal-footprint agent installed on the home router, we provide a holistic solution to manage the connected home network and protect it from internal and external security threats. Our unique technology can be deployed on virtually all the existing home gateways quickly and at a minimal cost, providing ISPs and router manufacturers with better visibility into home networks and a premium service that can be sold to customers to make their connected future simple, reliable and secure.

Manufacturing, Consulting, Business Services and Distribution & Logistics are the top four industries leading IoT adoption. Location intelligence, streaming data analysis, and cognitive BI are the top three most valuable IoT use cases.

Manufacturing, Consulting, Business Services and Distribution & Logistics are the top four industries leading IoT adoption.

Growing revenue and increasing competitive advantage are the highest priority Business Intelligence (BI) objectives IoT advocates or early adopters are pursuing today.

Location intelligence, streaming data analysis, and cognitive BI are the top three most valuable IoT use cases. The higher the BI adoption, the greater the probability of success with IoT initiatives.

53% of all respondents say that IoT is somewhat important with fewer than 15% saying it is critical or very important today.

These and many other insights are from Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series study. The study defines IoT as the network of physical objects, or “things,” embedded with electronics, software, sensors, and connectivity to enable objects to collect and exchange data. The study examines key related technologies such as location intelligence, end-user data preparation, cloud computing, advanced and predictive analytics, and big data analytics. Please see page 11 of the study for details regarding the methodology. For an excellent overview of Internet of Things (IoT) predictions for 2018, please see Gil Press’ post, 10 Predictions For The Internet Of Things (IoT) In 2018.

As digital technology infuses everyday life, it will change human behavior—raising new challenges about equality and fairness.

In a single generation, this has become the new normal: Nearly all adult Americans use the internet, with three-fourths of them having broadband access in their homes. And the internet travels with them in their pockets—95 percent have a cellphone, 81 percent have a smartphone. This ability to constantly connect has changed how people interact, especially in their social networks—more than two-thirds of adults are on Facebook or Twitter or another social media platform.

Digital innovations have made it easier for people to find more information than ever before, and made it easier to create and share material with others. From smartphone-delivered directions to voice-driven queries to on-demand news, people’s lives have been transformed by these technologies. Yet today’s inventions and innovations mark only the start, and tomorrow’s digital disruption, which is already underway, will probably dwarf them in impact.

The next digital evolution is the rise of the internet of things—sometimes now called the “internet on things.” This refers to the growing phenomenon of building connectivity into vehicles, wearable devices, appliances and other household items such as thermostats, as well as goods moving through business supply chains. It also covers the rapid spread of data-emitting or tracking sensors in the physical environment that give readouts on everything from crop conditions to pollution levels to where there are open parking spaces to babies’ breathing rates in their cribs.

The Pew Research Center and Elon University in North Carolina invited hundreds of technology experts in 2014 to predict the future of the internet by the year 2025, and the overriding theme of their answers addressed this reality. They predicted that the growth of the internet of things will soon make the internet like electricity—less visible, yet more deeply embedded in people’s lives, for good and for ill.

The internet of things will have literally life-changing impact on innovation and the application of knowledge in the coming years. Here are four major developments to anticipate.

The emergence of the ‘datacosm’

The spread of the internet of things will accelerate the digitization of data, spawning creation of record amounts of information. Data and connectivity will be ubiquitous in an environment sometimes called the “datacosm”— a term used to describe the importance of data, analytics, and algorithms in technology’s evolution. As previous information revolutions have taught us, once people—and things—get more connected, their very nature changes.

“When we are connected, power shifts. It changes who we are, what we might expect, how we might be manipulated, attacked, or enriched,” writes Joshua Cooper Ramo in his new book, The Seventh Sense. Networks of constant connection “destroy the nature of even the most solid-looking objects.” Connected things and connected people become more useful, more powerful, but also more hair-trigger and more destructive because their power is multiplied by a networking effect. The more connections they have, the more capacity they have for good and harmful purposes.

On the human level, the datacosm arising from the internet of things could function like a “fifth limb,” an extra brain lobe, and another layer of “skin” because it will be enveloping and omnipresent. People will have unparalleled self-awareness via their “lifestreams”: their genome, their current physical condition, their memories, and other trackable aspects of their well-being. Data ubiquity will allow reality to be augmented in helpful—and creepy—ways.

For instance, people will be able to look at others and, thanks to facial recognition and digital profiling, simultaneously browse their digital dossiers through an app that could display the data on “smart” contact lenses or a nearby wall surface. They will gaze at artifacts such as paintings or movies and be able to download material about how the art was created and the life story of the creator. They will take in landscapes and cityscapes and be able to learn quickly what transpired in these places long ago or what kinds of environmental problems threaten them. They will size up buildings and have an overlay of insight about what takes place inside them.

Part of the reason that data will be infused into so much is that the interfaces of connectivity and the ability to summon data will be radically enhanced. Human voices, haptic interfaces that can be manipulated by finger movements (think of the movie “Minority Report”), real-time language translators, data dashboards that give readouts on a user’s personally designed webpage, even, eventually, brain-initiated commands will make it possible for people to bring data into whatever surroundings they find themselves. Not only will this allow people to apply knowledge of all kinds to their immediate circumstances, but it will also advance analysts’ understanding of entire populations as their “data exhaust” is captured by their GPS-enabled devices and web clickstream activity.

Many experts in the Pew Research Center’s canvassings expect major benefits to emerge from this growth and spread of data, starting with the fact that knowledge will be ever-easier to apply to real-time decisions such as which custom-designed medicine a person should receive, or which commuting route to take to work. Beyond that, this data overlay and growing analytic power will allow swifter interventions when public health problems arise, weather emergencies threaten, environmental stressors mount, educational programs are introduced, and products are brought to the market.

This new reality will also cause major hardships. When information is superabundant, what is the best way to find the best knowledge and apply it to decisions? When so much personal data is captured, how can people retain even a sliver of privacy? What mechanisms can be created to overcome polarizing propaganda that can weaken societies? What are the right ways to avoid “fake news,” disinformation, and distracting sideshows in a world of info-glut?

Struggles over people’s “right relationship” to information will be one of the persistent realities of the 21st century.

Growing reliance on algorithms

The explosion of data has given prominence to algorithms as tools for finding meaning in data and using it to shape decisions, predict humans’ behavior, and anticipate their needs. Analysts such as Aneesh Aneesh of the University of Wisconsin, Milwaukee, foresee algorithms taking over public and private activities in a new era of “algocratic governance” that supplants the way current “bureaucratic hierarchies” make government decisions. Others, like Harvard University’s Shoshana Zuboff, describe the emergence of “surveillance capitalism” that gains profits from monetizing data captured through surveillance and organizes economic behavior in an “information civilization.”

The experts’ views compiled by the Pew Research Center and Elon University offer several broad predictions about the algorithmic age. They predicted that algorithms will continue to spread everywhere and agreed that the benefits of computer codes can lead to greater human insights into the world, less waste, and major safety advantages. A share of respondents said data-driven approaches to problem-solving will often improve on human approaches to addressing issues because the computer codes will be refined at much greater speeds. Many predicted that algorithms will be effective tools to make up for human shortcomings.

But respondents also expressed concerns about algorithms.

They worried that humanity and human judgment are lost when data and predictive modeling become paramount. These experts argued that algorithms are primarily created in pursuit of profits and efficiencies and that this can be a threat; that algorithms can manipulate people and outcomes; that a somewhat flawed yet inescapable “logic-driven society” could emerge; that code will supplant humans in decision-making and that, in the process, humans will lose skills and specialized, local intelligence in a world where decisions are based on more homogenized algorithms; and that respect for individuals could diminish.

Just as grave a concern is that biases exist in algorithmically organized systems that could worsen social divisions. Many in the expert sampling said that algorithms reflect the biases of programmers and that the data sets they use are often limited, deficient, or incorrect. This can deepen societal divides. Those who are disadvantaged could be even more so in an algorithm-organized future, especially if algorithms are shaped by corporate data collectors. That could limit people’s exposure to a wider range of ideas and eliminate serendipitous encounters with information.

A new relationship with machines and complementary intelligence

As data and algorithms permeate daily life, people will have to renegotiate the way they use and think about machines, which now are in a state of accelerating learning. Many experts see a new equilibrium emerging as people take advantage of artificial intelligence that can be consulted in an instant, context-aware gadgets that “read” a situation and assemble relevant information, robotic devices that serve their needs, smart assistants or bots (possibly in the form of holograms) that help people navigate the world or help represent them to others, and device-based enhancements to their bodies and brains. “Basically, it is the Metaverse from Snow Crash,” predicts futurist Stowe Boyd, referring to Neal Stephenson’s sci-fi vision of a world where people and their avatars seamlessly interact with other people, their avatars, and independent artificial intelligence agents developed by third parties, including corporations.

The creation and application of all this knowledge has vast implications for basic human activity—starting with cognition. The very act of thinking is already undergoing significant change as people learn how to tap into all this information and cope with processing it. That impact will expand in the future. The quality of “being” will change as people are able to be “with” each other via lifelike telepresence. People’s capacities are likely to expand as digital devices, prostheses, and brain-enhancing chips become available. Human behavior itself could change as an overlay of data gives people enhanced situational and self-awareness. The way people allocate their time and attention will be restructured as options proliferate. For instance, the manner in which they spend their leisure time is likely to be radically recast as people are able to amuse themselves in compelling new virtual worlds and enrich themselves with vivid new learning experiences.

Greater innovation in social norms, collective action, credentials, and laws

With so much upheaval ahead, people, groups, and organizations will be forced to adjust. At the level of social norms, it is easy to envision social environments in which people must constantly negotiate what information can be shared, what kinds of interruptions are tolerable, what balance of fact-checking and gossip is acceptable, and what personal multitasking is harmful. In other words, much of what constitutes civil behavior will be up for grabs.

At a more formal level, some primary aspects of collective action and power are already altered as social networks become a societal force, both as pathways of knowledge sharing and as mechanisms for mobilizing others to do something. There are new ways for people to collaborate and solve problems. Moreover, there are a growing number of group structures that address problems ranging from microniche matters (my neighbors and I respond to a local issue) to macroglobal wicked problems (multinational alliances tackle climate change and pandemics).

Shifts in labor markets in the knowledge economy, which are constantly pressing workers to acquire new skills, will probably refashion some of the features of higher education and prompt change in work-related training efforts. Fully 87 percent of current U.S. workers believe it will be important or essential for them to pursue new skills during their work lives. Not many believe the existing certification and licensing systems are up to that job. A notable number of experts in another Pew Research Center-Elon University canvassing are convinced that the training system will begin breaking into several parts: one that specializes in basic work preparation education to coach students in lifelong learning strategies; another that upgrades the capacity of workers inside their existing fields; and yet another that is more designed to handle the elaborate work of schooling those whose skills are obsolete.

At the most structured level, new laws and court battles are inevitable. They are likely to address questions such as: Who owns what information and can use it and profit from it? When something goes wrong with an information-processing system (say, a self-driving car propels itself off a bridge), who is responsible? Where is the right place to draw the line between data capture—that is, surveillance—and privacy? Can a certain level of privacy be maintained as an equal right for all, or is it no longer possible? What kinds of personal information are legitimate to consider in assessing someone’s employment, creditworthiness, or insurance status? Where should libel laws apply in an age when everyone can be a “publisher” or “broadcaster” via social media and when people’s reputations can rise and fall depending on the tone of a tweet? Can information transparency regimes be applied to those who amass data and create profiles from it? Who’s overseeing the algorithms that will be making so many decisions about what happens in society? (Several experts in the Pew Research Center canvassing called for new governmental regulations relating to the development and deployment of algorithms.) Which entities should define what is appropriate out-of-bounds speech for a community, a culture, a nation?

The information revolution in the digital age is magnitudes faster than those of previous ages. Much greater movement is occurring in technology innovation than in social innovation—and this potentially dangerous gap seems to be expanding. As we grapple with this, it would be useful to keep in mind the Enlightenment sensibility of Thomas Jefferson. He wrote in 1816: “Laws and institutions must go hand in hand with the progress of the human mind. As that becomes more developed, more enlightened, as new discoveries are made, new truths disclosed, and manners and opinions change with the change of circumstances, institutions must advance also, and keep pace with the times.”

We are likely to have to depend on our machines to help us figure out how to avoid being crushed by this avalanche.

Amazon Alexa can already turn off your lights and close your garage. Now it can also make your house smell like a Hawaiian vacation.

Prolitec, which calls itself a “scenting services company,” announced Monday that its Aera fragrance systems can now be voice controlled through the Amazon Echo smart speaker and other Alexa-compatible devices.

The Aera systems offer eight different fragrances, which range from pink grapefruit to basmati rice. The fragrance capsules can operate 24 hours a day and run for a full 60 days.

You can tell Alexa to turn Aera on, have Alexa raise or lower scent levels, or ask what the current scent levels are. If you already own an Aera, you can get it to work with Alexa by enabling the Aera skill in your Amazon Alexa app.

Aera is only the latest attempt to offer smart scents. In the 1950’s Hans Laube invented a “Smell-O-Vision” system for automated odor releases during movies. (Because who wouldn’t want to smell King Kong as he swings through New York?) And for the last 20 years, various companies have experimented with digitized scents that could be embedded in email or web pages.

MESH is a tool that let you explore the smart world using everyday objects.Just attach your MESH tag to any physical object, and connect it with various connected devices and Internet applications on the MESH app. Your own personal smart system is created, just like that!No matter what your knowledge level, MESH is easy to use. There is no need for electronics or programming expertise. Simply drag and drop to connect the icons on the MESH app.

Choosing an IoT platform is a pre-requisite for beginning the development of an end-to-end IoT solution. Let us take a look at Raspberry Pi and Arduino – the most popular open firmware and hardware platforms.

Arduino is a microcontroller board that is used for dedicated applications; for example, actuating small devices like motors, sensors, and lights. On the other hand, Raspberry Pi has a microcontroller, HDMI ports, and RAM. Which means that; with basic coding knowledge, you can configure an OS on Raspberry Pi and use it as a media streaming device, running a web server, or VPNs. So, if you are looking for an M2M interface, Arduino is what you need. But, if your end use involves a human interface then Raspberry Pi would serve the purpose.

Which other crucial metrics should you consider before choosing between Arduino and Raspberry Pi?

PowerRequirement

A typical Arduino uses an ATmega328 chip with 2KB RAM, 32 KB flash memory, and 1 KB EEPROM. The power consumption is thus fractional – you can use a 9V battery or just plug it into your computer. The power drawn can be further reduced by decreasing the Vcc voltage, reducing a clock source, turning off clocks to peripherals, or only triggering when an interrupt fires. Also, it does not require a shut-down process, while the code runs immediately when Arduino is plugged-in.

Raspberry Pi, as explained earlier, has a full-fledged computing system. It usually has a Linux OS, more than 512 RAM, 32 GB SD Card, USB and HDMI ports. It also requires a proper shut down process. As you can see, Raspberry Pi is like a low performance PC hardware system running on Linux; but comparatively lower power consumption.

Network connectivity

Raspberry Pi has a built-in Ethernet port as well as USB ports for connecting WiFi dongles. On the other hand, Arduino has no built-in network connectivity and requires additional hardware.

Sensor connectivity

Arduino has 14 digital and 6 analog I/O pins. It can thus be interfaced with sensors that measure pulse-width modulation, temperature, and similar Vcc to analog changes. Also, it has a scalable hardware design.

Raspeberry Pi has 8 I/O pins which are all digital. Chips like MCP3008 can be used for interfacing a Raspberry Pi with an analog input.

Development Languages

Arduino does not have an OS. So, coding and prototyping is done in C/C++ with the Arduino IDE. Raspberry Pi runs on an OS called Raspbian based on Debian Linux which lets you code in C/C++, Java, Python, .NET, PHP, NodeJS etc.

Amazon’s digital assistant Alexa might show up in a lot of new devices soon.

That’s because the online retail giant has decided to open up what amounts to Alexa’s ears, her 7-Mic Voice Processing Technology, to third party hardware makers who want to build the digital brain into their devices. The new development kit also includes access to Amazon’s proprietary software for wake word recognition, beamforming, noise reduction, and echo cancellation as well as reference client software for local device control and communication with the Alexa Voice Service.

The move will make it easier and less expensive for hardware makers to build Alexa into their products.

“Since the introduction of Amazon Echo and Echo Dot, device makers have been asking us to provide the technology and tools to enable a far-field Alexa experience for their products,” said Priya Abani, director of Amazon Alexa said in a statement. “With this new reference solution, developers can design products with the same unique 7-mic circular array, beamforming technology, and voice processing software that have made Amazon Echo so popular with customers. It’s never been easier for device makers to integrate Alexa and offer their customers world-class voice experiences.”

Amazon said the new development kit will be invitation only. Device makers can sign up here for an invite and to learn more about the technology.

A similar decision in 2015 to give developers the opportunity to build new capabilities for Alexa through the Alexa Skills Kit helped push Amazon into the early lead in the competitive voice assistant market. Developers who want to add to Alexa’s abilities can write code that works with Alexa in the cloud, letting the smart assistant do the heavy lifting of understanding and deciphering spoken commands.

The transformation of the healthcare industry has begun. While it will take many years, the shake-up in patient, provider and payer processes and analytics systems will leave the industry profoundly different.

On the horizon is a much more cost-efficient healthcare industry that offers truly personalized healthcare. Providers and patients will be able to leverage the ever-increasing medical knowledgebase and combine that with patient-specific historical and real-time data, including genetics, lifestyle behavior and environmental data.

The adoption of Internet of Things (IoT) networks, the data collected and the analytics of that data are accelerating the transformation of the healthcare industry.

Consumers utilizing home health technologies will increase from 14.3 million worldwide in 2014 to 78.5 million by 2020.

Over the next few years, patient monitoring devices will improve, and providers will increasingly implement IoT and big data analytics solutions. As a result, the global IoT healthcare market will grow at a significant rate.

Trends to watch

The following are some trends I am watching in 2016. Many are interrelated, and some are longer term than others. But all will be important to watch over the next 12 months.

Consumer-driven healthcare. Consumers are taking more responsibility for their own heath. As they do, they will demand better access to their data and improved health technology solutions that allow them to manage their own healthcare.

Digital healthcare transformation. Data from IoT devices, including hospital room sensors, lab equipment, employee wearables and patient monitoring devices will enable the industry to accelerate the transformation to digital. This transformation will cut healthcare costs and improve patient experiences and outcomes. Providers will increasingly look to analytics to provide predictive and prescriptive capabilities, dramatically improving the ability of healthcare providers to help patients. Payers will leverage that data to control costs and optimize patient healthcare outcomes.

Extracting insights from all the data. The amount of healthcare-related data available within the industry is growing exponentially. The IoT will result in an increased flow of data for patient records, population health data and other databases, bringing a new complexity to provider and physician operations. Too much data can overload those providing care and distract them from their mission of treating patients. Providers will seek help from professional IoT services firms to help them develop processes and IoT platforms that can extract insights from many data sources.

Remote patient monitoring. Expect new remote patient monitoring devices, wearable clothing and smartphone apps that analyze the data collected. We are at the beginning of a new era of remote patient monitoring that will automatically feed patient records with real-time data, perform analysis and send coaching notifications to both providers and patients. This will make healthcare easier, convenient, 24/7, web-enabled and personalized.

Providers begin shift toward remote healthcare. As consumers adopt remote monitoring devices, providers will restructure in order to provide remote medical care services and solutions. New processes, roles, and skills will be required. Larger providers will offer healthcare cognitive diagnostic and coaching mobile apps for patients to use remotely.

Creating baseline and benchmark databases. IoT emerges as a key data capture point to establish a common baseline of data for care teams to utilize when comparing treatment options. Teams of providers will leverage historical data and analytics to treat patients who have similar symptoms or diagnoses as those in the baseline data.

Patient centered analytics. Expect more focus on using advanced analytics, visualizations and decision support tools (e.g., Watson) to improve diagnostic accuracy. Both provider and patient versions of these tools should emerge. Treatments will become more precise, effective and personalized.

Cognitive coaching apps. Look for providers to begin releasing mobile apps that patients can use for healthcare and wellness coaching. Patients will increasingly demand these cognitive era apps, which will leverage data collected by wearables and information found in electronic health records. These apps will provide patients with personalized strategies to combat illness and behaviors in order to maintain a healthy lifestyle and manage their own health.

Government regulations. Governments will lay out guidelines for how medical apps (those apps that make medical recommendations and affect treatments of various diseases) will be regulated.

Better component technology. Innovation in IoT solution and network components (e.g., smaller sensors, faster CPUs at lower cost) and wearable medical devices will bring cheaper, more advanced medical devices that are much more accurate and can transmit many new health measurements to electronic health records.

Device interoperability and data integration. Analytics adoption in healthcare is closely tied to the ease with which disparate structured and unstructured data sources can be integrated and leveraged for data-driven decision making. As the number of medical-related IoT connected devices grows, the key challenge will be to ensure that data from all these devices can be read into big data platforms and then easily integrated into analytics solutions.

Security and privacy issues. IoT and wearable sensors are increasingly collecting patient specific data. The healthcare industry, vendors and governments need to figure out how to ensure all this private and personal data is secured appropriately. This is a significant challenge and one that will require collaboration from all involved parties.

Sharing of patient data. While security and privacy of patient healthcare records are critical, the fact is patients see multiple providers. Information must be shared across multiple providers in order to result in proper diagnosis, treatment and ongoing effective decision making. Sharing of information electronically can also serve to improve cost efficiencies throughout the healthcare system.

Integration of research, operational and IT analytics. Look for increased requirements to integrate data from many different internal and external sources. Researchers, business execs, doctors and IT professionals will collaborate to provide better overall care to patients. Vendors will increase their focus on integrating platforms, applications and data.

IoT for the hospital. Leading hospitals will develop long-term strategies to leverage sensors and wearables throughout their operations in order to build a real-time sense-and-respond intelligent operation that cuts costs and improves patient experiences and outcomes. Researchers, nurses and doctors will spend less time doing administrative work and more time with patients.

Skills gap. As the industry transforms toward digital, healthcare organizations will realize they don’t have all the data and analytics skills that are required. Competition for top-tier data scientists and related talent will remain a pervasive industry pain point for healthcare providers and payer organizations.

Leadership challenges. There is a growing need for data-driven vision and leadership in the executive ranks within the healthcare industry. The industry needs executives who understand the value that IoT and analytics will bring to the industry. Vendors can help push this transformation with an increased focus on the benefits of analytics.

As you can see, a lot will be happening in 2016 around the intersection of healthcare and the IoT. Key drivers will be an increasing demand for advanced healthcare information systems that can cut costs and drive improved patient-centered care.

The Internet of Things (IoT) is disrupting businesses, governments, and consumers and transforming how they interact with the world. Companies are going to spend almost $5 trillion on the IoT in the next five years — and the proliferation of connected devices and massive increase in data has started an analytical revolution.

To gain insight into this emerging trend, BI Intelligence conducted an exclusive Global IoT Executive Survey on the impact of the IoT on companies around the world. The study included over 500 respondents from a wide array of industries, including manufacturing, technology, and finance, with significant numbers of C-suite and director-level respondents.

Through this exclusive study and in-depth research into the field, BI Intelligence details the components that make up IoT ecosystem. We size the IoT market in terms of device installations and investment through 2021. And we examine the importance of IoT providers, the challenges they face, and what they do with the data they collect. Finally, we take a look at the opportunities, challenges, and barriers related to mass adoption of IoT devices among consumers, governments, and enterprises.

Here are some key takeaways from the report:

We project that there will be a total of 22.5 billion IoT devices in 2021, up from 6.6 billion in 2016.

We forecast there will be $4.8 trillion in aggregate IoT investment between 2016 and 2021.

It highlights the opinions and experiences of IoT decision-makers on topics that include: drivers for adoption; major challenges and pain points; stages of adoption, deployment, and maturity of IoT implementations; investment in and utilization of devices, platforms, and services; the decision-making process; and forward- looking plans.

In full, the report:

Provides a primer on the basics of the IoT ecosystem

Offers forecasts for the IoT moving forward and highlights areas of interest in the coming years

To get your copy of this invaluable guide to the IoT, choose one of these options:

Subscribe to an ALL-ACCESS Membership with BI Intelligence and gain immediate access to this report AND over 100 other expertly researched deep-dive reports, subscriptions to all of our daily newsletters, and much more. >> START A MEMBERSHIP

Purchase the report and download it immediately from our research store. >> BUY THE REPORT

The choice is yours. But however you decide to acquire this report, you’ve given yourself a powerful advantage in your understanding of the IoT.

In this video, “Hello, Alexa!”, we’re going to introduce the Alexa Skills Kit and teach you how to create skills, which are voice driven applications for Alexa. We will build and deploy a basic skill. This skill will be called the “Greeter” skill, and will say hello to users when they invoke the skill using the words that we specify.

Former Amazon executive John Rossman shares his checklist for developing an internet of things strategy for your organization.

The internet of things (IoT) may present the biggest opportunity to enterprises since the dawn of the internet age, and perhaps it will be bigger. Research firm Gartner predicts there will be nearly 20 billion devices on the IoT by 2020, and IoT product and service suppliers will generate $300 billion+ in revenue.

“In the course of my career, I’ve estimated and planned hundreds of projects,” John Rossman, who spent four years launching and then running Amazon’s Marketplace business (which represents more than 50 percent of all Amazon units sold today), writes in his new book, The Amazon Way on IoT: 10 Principles for Every Leader from the World’s Leading Internet of Things Strategies. “I’ve learned that, even before you start seeking answers, it’s imperative to understand the questions. Guiding a team to a successful outcome on a complex project requires understanding of the steps and deliverables, necessary resources, and roles and every inherent risk and dependency.”

Before you start the hardware and software design, and before you figure out how to engage developers, he says, you need to start with a better set of questions.

Rossman says there are three key phases to building a successful IoT strategy. While he presents the steps sequentially, he notes that many steps are actually taken concurrently in practice and can be approached in many different ways.

Part 1. Develop and articulate your strategy

First and foremost, Rossman says, you must narrow and prioritize your options. IoT presents a broad swathe of opportunities. Success depends upon understanding your market, evaluating the opportunities with deliberation and attacking in the right place.

Landscape analysis

It all begins with a landscape analysis. You need to thoroughly understand your industry and competitors — strengths, weaknesses, opportunities and threats (SWOT). This will help you see the megatrends and forces at play in your market.

“Creating a landscape analysis and value chain of your industry is a very important thing to do,” Rossman tells CIO.com. “Studying the market: What are they saying about IoT in your industry? Truly understanding what is your worst customer moment: Where do customers get frustrated? What data or what event improves that customer experience? What’s the sensor or IoT opportunity that provides that data?”

Value-chain analysis and profit-pool analysis

The next step, Rossman says, is to create a value-chain analysis and profit-pool analysis of your industry. It should be a broad view of the industry, don’t give in to tunnel-vision with a narrow view of your current business. In some cases, this may involve launching a business in one part of the value chain as a way to gain perspective on the rest of the value chain and to identify other business opportunities.

Partner, competitor and vendor analysis

Create a map of other solutions providers in your space to develop a clear understanding of what exactly each one does, who their key clients are and what their IoT use cases are. Rossman says you should even pick a few to interview. Use this process to understand the needs of customers, the smart way those needs are already being met and where the gaps are.

Customer needs

The next step, Rossman says, is to document specific unmet customer needs and identify the key friction points your future customers are currently experiencing.

“Following the path from start to your desired outcome can help you identify details and priorities that might otherwise be dealt with at too high a level or skipped over entirely,” he writes.

Rossman warns that crafting strong customer personas and journeys is hard work, and you may need to start over several times to get it right.

“The biggest mistake you can make on these is to build them for show rather than for work,” he writes. “Don’t worry about the beauty of these deliverables until things are getting baked (if at all). Do worry about getting at insights, talking to customers and validating your findings with others who can bring insights and challenges to your work.”

Evaluation framework and scoring

Design ways to assess the success of your work.

“This includes understanding a project’s feasibility and transition points and how it will tie into other corporate strategies at your company,” Rossman writes. “Sometimes, especially if your organization is new to the field of connected devices, the success of your project should be measured in terms of what you can learn from the project rather than whether or not it can be classically considered a success.”

You might undertake some early IoT initiatives purely to gain experience, with no expected ROI, he says.

Strategy articulation

Once you have all these analyses under your belt, you need share what you’ve learned with the rest of your team. Rossman says he’s had the most success articulating these learnings by building a flywheel model of business systems and by developing a business model.

Part 2. Build your IoT roadmap

Once you’ve explained your big idea and why your organization should pursue it, you need an IoT roadmap that helps you plan and communicate to others what the journey will be like, what is being built and how it will work.

In other words, you need a big vision, but you don’t want to “bet big.” Make small bets to test your thinking. This can involve creating a prototype, a minimally viable product or jointly developing a project with existing customers and partners.

Rossman suggests four methods that can help you articulate your roadmap:

The future press release. Develop a simple but specific product announcement. This forces you to clarify your vision, Rossman says.

A FAQ for your IoT plan. Forecast some of the questions you’re likely to get about your product and create a frequently asked questions (FAQ) document to answer them.

A user manual. Develop a preliminary user manual for your IoT device. It should address the end user. If the product includes an API, you should also build a user manual for the developer.

A project charter. Write a project charter. This is a written project overview that outlines the key facets of the project. It should help you understand the resources you need to undertake the project, what the key milestones are and the schedule.

Part 3. Identify and map your IoT requirements

The last step is to identify and map your IoT requirements — the technical capabilities you need to make your solution a success.

“Companies use many different types of approaches, such as use cases, user stories, process flows, personas, architecture specifications and so on to document their requirements,” Rossman writes.

Regardless of the requirements methodology you settle on, Rossman says it’s important to answer questions around insights (data and events), analytics and recommendations, performance and environment and operating costs.

For example, under ‘insights,’ it’s important to answer questions like these:

What problem, event or insight is the end user solving for?

What insights would be valuable to the customer?

What recommendation or optimization using the data would be valuable to a customer?

What data needs to be collected?

Analytics and recommendations questions might include the following:

How responsive will “adjustments” or optimizations need to be (specify in time range)?

How complex will the “math” be? Write the math equation or pseudologic code if you can.

Will notifications, logic, “math,” or algorithms be consistent and fixed, or will they need to be configurable, updated and managed?

Performance questions might include these:

Estimate the amount of data transmitted over a period of time (hour, day).

What are the consequences of data not being collected?

What are the consequences of data being collected but not transmitted?

Environment and operating requirements questions might include these:

What operating conditions will the device and sensor be in? Temperature, moisture, pressure, access and vibration are example conditions.

What device physical security needs or risks are there?

Will the IoT device or sensors be embedded within another device, or will they be independent and a primary physical device themselves?

Costs questions might include these:

What is the cost per device target range?

What is the cost per device for connectivity target range?

What is the additional operating cost range the business can support for ongoing operating infrastructure?

“As you build your plans, remember that though IoT can provide key pieces to the puzzle, it’s no golden ticket,” Rossman writes. “Simply creating an IoT solution will not bring you success. However, if you focus on providing strong value to your customers through new or updated products and services, improving company operations or creating new or more-efficient business models, you’ll be much more likely to find success.”

Since the creation of the first web page, the connected world has been constantly changing at a rapid pace, speeding its way through Web 2.0 and propelling us into the future. That future is now. The Internet of Things (IoT) is taking shape, and it’s ushering in the third major evolution of the internet.

If you don’t catch the wave, you could miss out on the Internet of Things and the huge boom that’s coming for entrepreneurs in nearly every industry.

Take a look at just a few powerful data points on the Internet of Things:

Parks Associates analysts expect that almost 55 million smart home devices will be sold to U.S. broadband households in 2020.

While 2016 was a big year for IoT, 2017 will be even bigger. Positioning yourself early is everything when it comes to capitalizing on the next evolution of the internet. Here are the top trends you can expect to see in 2017.

Voice assistants will dominate product sales

Amazon’s success with Echo and Alexa, the speaker’s virtual voice assistant, has been astounding. There’s little doubt that Amazon has penetrated the mass market, with Echo finding its way into the hands of owners who wouldn’t even know to call it a Smart Home product.

This trend will continue in a big way. The Google Home voice-activated speaker and personal assistant is growing the product category in terms of both sales and innovation. While Amazon has the advantage of having made the first move, Google Home is offering a deep integration into digital life by syncing directly with the owner’s Google account. It also benefits from Google’s extensive experience in machine learning, artificial intelligence and data analysis. Also, look for Microsoft to make similar moves with Cortana.

Smart City will be the new Smart Home

Visions of the Smart City are starting to materialize as CTO’s for major municipalities are coming to understand how Internet of Things products and services can provide cost savings, increase quality of life and promote safety in urban environments. Keep an eye out for the appearance of smart lighting, connected streets, smart parking, smart meters, connected apartments and on-demand services in the most innovative cities.

Hardware-based hubs have a hard time

Hub-based ecosystems were all the rage three years ago. The rise in virtual-assistants, however, is threatening hub-based platforms.

There are two reasons for this. The first is that voice-driven assistants (like Amazon’s Alexa and the Google Home) connect to devices in the cloud and therefore don’t require an additional array of radios inside a separate hub. Secondly, more and more routers are being equipped with wireless capabilities like Z-wave, Zigbee and BLE, which further reduce the need for additional hardware.

The Smart Home will go mainstream

The success of Amazon’s Echo rapidly accelerated the adoption of Smart Home technology for everyday consumers, but it’s not the only reason that mass consumers are embracing the concept of the Smart Home. Smart Home product and service developers are making better products, many of which include better education and better support.

Additionally, IoT companies are continually getting better about understanding who their customers are and what they want. As consumer preferences become apparent, product companies are telling better stories that communicate real value to their customers.

Voice is the new UI

The ability to command the Echo’s speaker via Alexa’s voice-recognition system introduced a new way for consumers to interact with the electronic world around them: voice.

While Siri may have initiated voice-activation with Apple products back in 2011, Alexa’s voice capabilities (or “skills”) could very well replace the smartphone touch-screen over time. Expect this trend to continue as other connected products add to Alexa’s voice capabilities, which also allow you to control non-Amazon products–even your car.

Evolving business models (more services)

Two years ago, product companies were focused on connecting hardware (like lights, locks, doorbells, etc.) to the internet. Last year, the focus was on integrating those products with smart hubs and other connected point-solutions. This year, expect product companies to focus on providing services in an attempt to diversify their revenues and achieve recurring cash flows.

Wearables will work with the Smart Home

This will be the year that wearables converge with the Smart Home. Imagine a day when your fitness tracker won’t let you turn on your TV because you didn’t exercise yet. This convergence of industries presents a great opportunity for services and apps.

How to stay ahead

The IoT market is moving at breakneck speed; if you want to be a part of it, you need to stay ahead. Here are two ways to do that:

Join an industry group if you have a company in the space. SkyBell (my IoT startup) is a member of the Internet of Things Consortium (IoTC), a nonprofit advocacy group that is looking to expand consumer awareness around IoT. The IoTC provides me with abundant opportunities to network with leaders in the Smart Home industry and stay on top of the latest trends.

Unless you have been living under the proverbial rock, you probably heard about a number of Internet of Things (IoT) attacks this fall, beginning with KrebsOnSecurity, then OVH, then the DDoS attack on Dyn DNS. All of this started with a bot called Mirai, and involved IoT devices. Why is this important? By 2020, it is estimated that the number of connected devices is expected to grow exponentially to 50 billion. A survey by HP indicates that about 70% of these devices have vulnerabilities, making them the perfect targets for botnets like Mirai.

Below is a collection of 10 blogs written by industry experts on this topic, that will help you fully understand the implications of this botnet and what it means for the future of connected devices.

Internet of Things or Internet of Threats? IoT is the ability for devices to be connected the Internet and communicate with other devices – think a thermostat knowing automatically when to heat your home without you having to take an action. While these smart devices may seem like a brilliant idea that can save you time and money, there are also risks associated with them. This blog will walk you through the two-part dilemma that is faced when it comes to using these devices and provide a background of the IoT.

Nine Questions to Ask to Determine IoT Device Safety: If you’re familiar with the IoT, then you’re aware of some of the risks that come with connected devices. From January 5-8, consumers and reporters alike will be flooding Las Vegas, Nevada for the Consumer Electronics Show to learn more about new devices making their debut in 2017. This blog by APAC Security Evangelist David Hobbs will provide nine questions you should ask the manufacturers (regardless of whether you are a consumer or reporter) about the safety of these devices.

BusyBox Botnet Mirai – the warning we’ve all been waiting for? Radware’s EMEA Security Evangelist, Pascal Geenens, takes us back to where it began – the attack on KrebsOnSecurity. As he states, “The most concerning fact, and the genius of Mirai, resides in its simplicity for victimizing IoT devices.” This blog will outline how the Mirai botnet works.

The deplorable state of IoT security: Following the public release of Mirai, the security community began to grow extremely concerned about the potential for additional attacks of that nature. In his second blog, Pascal discusses how the state of IoT security presents a prime opportunity for more attacks.

How Friday’s Massive DDoS Attack on the U.S. Happened: DNS servers are a like a roadmap to the internet and help users find the websites they are looking for. When an attacker ties up all of the DNS’s resources, legitimate clients are unable to resolve their request. Radware’s ERT Researcher, Daniel Smith, outlines how the attack on Dyn DNS happened in this blog.

Let’s discuss facts: An insight into Mirai’s source-code: After three major cyber-attacks, speculation abounded on who the attackers were, what their motivation was, the exact attack vectors and the traffic volumes. In this blog post, Radware’s Snir Ben Shimol discusses what we know to be the facts about these attacks.

Is Heat Your Thermostat’s First Priority? Remember that smart thermostat that we mentioned? A hacker performed a DDoS attack on a heating distribution system that controlled the heating of two large apartment blocks in Finland back in November, shutting off heat for 20,000 residents. In the Dyn DNS attack, it was discovered that a handful of connected devices, mainly IP cameras, DVRs and routers, were the ones infected by Mirai and used in the attack. In this blog, Pascal discusses how that relates to your smart devices, like thermostats, and whether you should be concerned.

Cyber Security Predictions: Looking Back at 2016, Peering Ahead to 2017: What do we see on the docket for 2017? We correctly predicted in the 2015–2016 Global Application and Network Security Report that we would see the rise of the Internet of Things, which spawned the largest DDoS attack in history. Radware’s Vice President of Security Solutions, Carl Herberger, discusses our predictions for 2017 in this blog post.

The conversation is still going on the record-breaking volume of the Mirai botnet attack, and doesn’t show signs of slowing. Many security executives have been warning about IoT threats such as this for years, and now the world is finally paying attention.

As we go into 2017 our IoT Analytics team is again evaluating the main IoT developments of the past year in the global “Internet of Things” arena. This article highlights some general IoT 2016 observations as well as our top 8 news stories, with a preview for the new year of opportunities and challenges for global IoT businesses. (For your reference, here is our 2015 IoT year in review article.)

In 2016 the main theme for IoT was the shift from hype to reality. While in 2015, most people only heard about IoT in the media or consumed some marketing blogs, 2016 was different. Many consumers and enterprises went out and started their own IoT endeavors or bought their own IoT devices. Both consumer IoT and enterprise IoT enjoyed record uptake, but also saw some major setbacks.

A. General IoT 2016 observations

A1. Consumer IoT

Millions of consumers bought their first IoT Device in 2016. For many of them this was Amazon Echo (see below for more details).

Unfortunately many consumers also realized that marketing promises and reality are often still disparate. Cases of disappointed users are increasing (For example a smart thermostat user who discovered that his thermostat was disconnected for a day).

Some companies were dissolved in 2016 (like the Smart Home Hub Revolvin April – causing many angry customers), others went bankrupt (like the smart watch maker Pebblein December) or didn’t even come to life at all (such as the augmented reality helmet startup Skullythat enjoyed a lot of publicity, but filed for bankruptcy in August without having sold a single product).

A2. Enterprise IoT

On the enterprise/industrial side of things, IoT 2016 will go down as the year many firms got real about their first IoT pilot projects.

A general wake-up call came in September when a massive cybersecurity attack that involved IoT devices (mainly CCTV cameras) shut down DNS provided Dyn and with it their customer’s websites (e.g., AirBnB, Netflix and Twitter). While this kind of attack didn’t directly affect most IoT companies, its implications scared many IT and IoT decision-makers. As a result, many IoT discussions have now shifted towards cybersecurity solutions.

B. Top 8 IoT 2016 Stories

For us at IoT Analytics, the IoT Security Attack on Dyn servers qualifies as the #1 story of the year. Here are our top takeaways from IoT 2016:

1. Biggest overall story: IoT Security attack on Dyn servers

The Dyn DDoS attack was the first large-scale cybersecurity attack that involved IoT devices – Dyn estimates that 100,000 infected IoT devices were involved. As a first-of-a-kind, it sent shockwaves through corporate IT and IoT.

Chinese CCTV system manufacturer, Hangzhou Xiongmai Technology Company, was at the core of the attack. Its cameras (among others) were infected with the so-called Mirai malware. This allowed the hackers to connect to the infected IoT devices and launch a flood of well-timed massive requests on Dyn servers – which led to the shutdown of their services.

2. Biggest Consumer IoT Success: Amazon Echo

Launched in June 2015, the Amazon Echo Smart Home Voice Control was undoubtedly the consumer IoT success story of the year. Recent data provided by Amazon reveals that device sales explodedby 9x (year-on-year vs. last Christmas).

Amazon sold more than 1 million Echo devices in December 2016

Our app-based Smart Home models confirm this trend suggesting that Amazon sold more than 1 million Echo devices in December 2016 and close to 4 million devices throughout the whole of 2016.

With these gains, Amazon has suddenly become the #1 Smart Home Hub and is leading the paradigm shift towards a voice-controlled automated home. Google jumped on the same train in October by releasing Google Home; Microsoft Home Hub is expected to follow in 2017.

3. Most overcrowded space: IoT Platforms

When we launched our coverage of IoT Platforms in early 2015, little did we know that the topic would soon become the hottest IoT area. Our count of platform providers in May 2016 showed 360 platforms. Our internal research is now well over 400. IoT Platforms is also well placed in the Gartner Hype Cycle 2016.

Companies have realized that the value of IoT lies in the data and that those that manage this data will be the ones capturing a large chunk of this value. Hence, everyone is building an IoT platform.

The frightening part is not necessarily the number but rather the fact that the sales pitches of the platform providers all sound like this: “We are the only true end-2-end platform which is device-agnostic and completely secure”.

4. Largest M&A Deal: Qualcomm/NXP

While we can see a massive expansion of global IoT software/analytics and platform offerings, we are also witnessing a consolidation among larger IoT hardware providers – notably in the chip sector. In October 2016, US-based chipmaker Qualcommannounced it would buy the leader in connected car chips NXP for $39B, making it the biggest-ever deal in the semiconductor industry.

Other large hardware/semiconductor acquisitions and mergers during IoT 2016 include Softbank/ARM ($32B) and TDK/Invensense ($1.3B)

5. Most discussed M&A Deal: Cisco/Jasper

In February, Cisco announced that it would buy IoT Platform provider Jasper Technologies for $1.4B. Journalists celebrated the acquisition as a logical next step for Cisco’s “Internet of Everything” story – combining Cisco’s enterprise routers with Jasper’s backend software for network operators and hopefully helping Cisco put an end to declining hardware sales.

6. Largest startup funding: Sigfox

Sigfox already made it into our 2015 IoT news list with their $100M Series D round. Their momentum and the promise of a global Low Power Wide Area Network led to an even larger funding round in 2016. In November, the French-based company received a record $160M in a Series E that involved Intel Capital and Air Liquide among others.

Another notable startup funding during IoT 2016 involved the IoT Platform C3IoT. The Redwood City based company received $70M in their Series D funding.

7. Investment story of the year: IoT Stocks

For the first time IoT stocks outperformed the Nasdaq significantly. The IoT & Industry 4.0 stock fund (Traded in Germany under ISIN: DE000LS9GAC8) is up 17.5% year-on-year, beating the Nasdaq which is up 9.6% in the same time frame. Cloud service providers Amazon and Microsoft are up 14% for the year, IoT Platform provider PTC is up 35%. Even communication hardware firm Sierra Wireless started rebounding in Q4/2016.

Some of the IoT 2016 outperformance is due to an increasing number of IoT acquisitions (e.g., TDK/Invensense). At the beginning of 2016 we asked if the underperformance of IoT stocks in 2015 was an opportunity in 2016. In hindsight, the answer to that question is “Yes”. Will the trend continue in 2017?

8. Most important government initiative: EU Data Protection policy

In May, the European Union passed the General Data Protection Regulation (“GDPR”) which will come into effect on 25 May 2018. The new law has a wide range of implications for IoT technology vendors and users. Among other aspects:

Security breaches must be reported

Each IoT user must provide explicit consent that their data may be processed

Each user must be given the right to object to automated decision making

Data coming from IoT Devices used by children may not be processed

From a security and privacy policy point of view the law is a major step forward. IoT technology providers working in Europe and around the world now need to revisit their data governance, data privacy and data security practices and policies.

C. What to expect in 2017:

War for IoT platform leadership. The large IoT platform providers are gearing up for the war for IoT (platform) leadership. After years of organic development, several larger vendors started buying smaller platform providers in 2016, mainly to close existing technology gaps (e.g., GE-Bitstew, SAP-Plat.one, Microsoft-Solair)

War for IoT connectivity leadership. NB-IoT will finally be introduced in 2017. The new low-power standard that is heavily backed by major telco technology providers will go head-to-head with existing LPWAN technology such as Sigfox or LoRa.

AR/VR becoming mainstream. IoT Platform providers PTC (Vuforia) and Microsoft (Hololens) have already showcased a vast range of Augmented Reality / Virtual Reality use cases. We should expect the first real-life use cases emerging in 2017.

Even more reality and less hype. The attention is shifting from vendor/infrastructure topics such as what the next generation of platforms or connectivity standards will look like and towards actual implementations and use cases. While there are still major developments the general IoT audience will start taking some of these technology advancements for granted and focus on where the value lies. We continue to follow that story and will update our list of IoT projects

Our IoT coverage in 2017: Subscribe to our newsletter for continued coverage and updates. In 2017, we will keep our focus on important IoT topics such as IoT Platforms, Security and Industry 4.0 with plenty of new reports due in Q1/2017. If you are interested in a comprehensive IoT coverage you may contact us for an enterprise subscription to our complete IoT research content.

The end of year or beginning of year is always a time when we see many predictions and forecasts for the year ahead. We often publish a selection of these to show how tech-based innovation and economic development will be impacted by the major trends.

A number of trends reports and articles have bene published – ranging from investment houses, to research firms, and even innovation agencies. In this article we present headlines and highlights of some of these trends – from Gartner, GP Bullhound, Nesta and Ovum.

Artificial intelligence will have the greatest impact

GP Bullhound released its 52-page research report, Technology Predictions 2017, which says artificial intelligence (AI) is poised to have the greatest impact on the global technology sector. It will experience widespread consumer adoption, particularly as virtual personal assistants such as Apple Siri and Amazon Alexa grow in popularity as well as automation of repetitive data-driven tasks within enterprises.

Online streaming and e-sports are also significant market opportunities in 2017 and there will be a marked growth in the development of content for VR/AR platforms. Meanwhile, automated vehicles and fintech will pose longer-term growth prospects for investors.

The report also examines the growth of Europe’s unicorn companies. It highlights the potential for several firms to reach a $10 billion valuation and become ‘decacorns’, including BlaBlaCar, Farfetch, and HelloFresh.

Alec Dafferner, partner, GP Bullhound, commented, “The technology sector has faced up to significant challenges in 2016, from political instability through to greater scrutiny of unicorns. This resilience and the continued growth of the industry demonstrate that there remain vast opportunities for investors and entrepreneurs.”

Big data and machine learning will be disruptors

Advisory firm Ovum says big data continues to be the fastest-growing segment of the information management software market. It estimates the big data market will grow from $1.7bn in 2016 to $9.4bn by 2020, comprising 10 percent of the overall market for information management tooling. Its 2017 Trends to Watch: Big Data report highlights that while the breakout use case for big data in 2017 will be streaming, machine learning will be the factor that disrupts the landscape the most.

Key 2017 trends:

Machine learning will be the biggest disruptor for big data analytics in 2017.

Making data science a team sport will become a top priority.

IoT use cases will push real-time streaming analytics to the front burner.

The cloud will sharpen Hadoop-Spark ‘co-opetition’.

Security and data preparation will drive data lake governance.

Intelligence, digital and mesh

In October, Gartner issued its top 10 strategic technology trends for 2017, and recently outlined the key themes – intelligent, digital, and mesh – in a webinar. It said that autonomous cars and drone transport will have growing importance in the year ahead, alongside VR and AR.

“It’s not about just the IoT, wearables, mobile devices, or PCs. It’s about all of that together,” said Cearley, according to hiddenwires magazine. “We need to put the person at the canter. Ask yourself what devices and service capabilities do they have available to them,” said David Cearley, vice president and Gartner fellow, on how ‘intelligence everywhere’ will put the consumer in charge.

“We need to then look at how you can deliver capabilities across multiple devices to deliver value. We want systems that shift from people adapting to technology to having technology and applications adapt to people. Instead of using forms or screens, I tell the chatbot what I want to do. It’s up to the intelligence built into that system to figure out how to execute that.”

Intelligent apps: using AI, there will be three areas of focus — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered immersive, conversational and continuous interfaces.

Intelligent things, as they evolve, will shift from stand-alone IoT devices to a collaborative model in which intelligent things communicate with one another and act in concert to accomplish tasks.

Virtual and augmented reality: VR can be used for training scenarios and remote experiences. AR will enable businesses to overlay graphics onto real-world objects, such as hidden wires on the image of a wall.

Digital twins of physical assets combined with digital representations of facilities and environments as well as people, businesses and processes will enable an increasingly detailed digital representation of the real world for simulation, analysis and control.

Blockchain and distributed-ledger concepts are gaining traction because they hold the promise of transforming industry operating models in industries such as music distribution, identify verification and title registry.

Conversational systems will shift from a model where people adapt to computers to one where the computer ‘hears’ and adapts to a person’s desired outcome.

Mesh and app service architecture is a multichannel solution architecture that leverages cloud and serverless computing, containers and microservices as well as APIs (application programming interfaces) and events to deliver modular, flexible and dynamic solutions.

Digital technology platforms: every organization will have some mix of five digital technology platforms: Information systems, customer experience, analytics and intelligence, the internet of things and business ecosystems.

Adaptive security architecture: multilayered security and use of user and entity behavior analytics will become a requirement for virtually every enterprise.

The real-world vision of these tech trends

UK innovation agency Nesta also offers a vision for the year ahead, a mix of the plausible and the more aspirational, based on real-world examples of areas that will be impacted by these tech trends:

Computer says no: the backlash: the next big technological controversy will be about algorithms and machine learning, which increasingly make decisions that affect our daily lives; in the coming year, the backlash against algorithmic decisions will begin in earnest, with technologists being forced to confront the effects of aspects like fake news, or other events caused directly or indirectly by the results of these algorithms.

The Splinternet: 2016’s seismic political events and the growth of domestic and geopolitical tensions, means governments will become wary of the internet’s influence, and countries around the world could pull the plug on the open, global internet.

A new artistic approach to virtual reality: as artists blur the boundaries between real and virtual, the way we create and consume art will be transformed.

Blockchain powers a personal data revolution: there is growing unease at the way many companies like Amazon, Facebook and Google require or encourage users to give up significant control of their personal information; 2017 will be the year when the blockchain-based hardware, software and business models that offer a viable alternative reach maturity, ensuring that it is not just companies but individuals who can get real value from their personal data.

Next generation social movements for health: we’ll see more people uniting to fight for better health and care, enabled by digital technology, and potentially leading to stronger engagement with the system; technology will also help new social movements to easily share skills, advice and ideas, building on models like Crohnology where people with Crohn’s disease can connect around the world to develop evidence bases and take charge of their own health.

Vegetarian food gets bloodthirsty: the past few years have seen growing demand for plant-based food to mimic meat; the rising cost of meat production (expected to hit $5.2 billion by 2020) will drive kitchens and laboratories around the world to create a new wave of ‘plant butchers, who develop vegan-friendly meat substitutes that would fool even the most hardened carnivore.

Lifelong learners: adult education will move from the bottom to the top of the policy agenda, driven by the winds of automation eliminating many jobs from manufacturing to services and the professions; adult skills will be the keyword.

Classroom conundrums, tackled together: there will be a future-focused rethink of mainstream education, with collaborative problem solving skills leading the charge, in order to develop skills beyond just coding – such as creativity, dexterity and social intelligence, and the ability to solve non-routine problems.

The rise of the armchair volunteer: volunteering from home will become just like working from home, and we’ll even start ‘donating’ some of our everyday data to citizen science to improve society as well; an example of this trend was when British Red Cross volunteers created maps of the Ebola crisis in remote locations from home.

In summary

It’s clear that there is an expectation that the use of artificial intelligence and machine learning platforms will proliferate in 2017 across multiple business, social and government spheres. This will be supported with advanced tools and capabilities like virtual reality and augmented reality. Together, there will be more networks of connected devices, hardware, and data sets to enable collaborative efforts in areas ranging from health to education and charity. The Nesta report also suggests that there could be a reality check, with a possible backlash against the open internet and the widespread use of personal data.

You don’t need Sherlock Holmes to tell you that cloud computing is on the rise, and that cloud traffic keeps going up. However, it is enlightening to see the degree by which it is increasing, which is, in essence, about to quadruple in the next few years. By that time, 92% percent of workloads will be processed by cloud data centers; versus only eight percent being processed by traditional data centers.

Cisco, which does a decent job of measuring such things, just released estimates that shows cloud traffic likely to rise 3.7-fold by 2020, increasing 3.9 zettabytes (ZB) per year in 2015 (the latest full year data for which data is available) to 14.1 ZB per year by 2020.

The big data and associated Internet of Things are a big part of this growth, the study’s authors state. By 2020, database, analytics and IoT workloads will account for 22% of total business workloads, compared to 20% in 2015. The total volume of data generated by IoT will reach 600 ZB per year by 2020, 275 times higher than projected traffic going from data centers to end users/devices (2.2 ZB); 39 times higher than total projected data center traffic (15.3 ZB).

Public cloud is growing faster than private cloud growth, the survey also finds. By 2020, 68% (298 million) of the cloud workloads will be in public cloud data centers, up from 49% (66.3 million) in 2015. During the same time period, 32% (142 million) of the cloud workloads will be in private cloud data centers, down from 51% (69.7 million) in 2015.

As the Cisco team explains it, much of the shift to public cloud will likely be part of hybrid cloud strategies. For example, “cloud bursting is an example of hybrid cloud where daily computing requirements are handled by a private cloud, but for sudden spurts of demand the additional traffic demand — bursting — is handled by a public cloud.”

The Cisco estimates also show that while Software as a Service (SaaS, for online applications) will keep soaring, there will be less interest in Infrastructure as a Service (IaaS, for online servers, capacity, storage). By 2020, 74% of the total cloud workloads will be software-as-a-service (SaaS) workloads, up from 65% at this time. Platform as a Service (PaaS, for development tools, databases, middleware) also will see a boost — eight percent of the total cloud workloads will be PaaS workloads, down from nine percent in 2015. However, IaaS workloads will total 17% of the total cloud workloads, down from 26%.

The Cisco analysts explain that the lower percentage growth for IaaS may be attributable to the growing shift away from private cloud to public cloud providers. For starters, IaaS was far less disruptive to the business — a rearrangement of data center resources, if you will. As SaaS offerings gain in sophistication, those providers may offer IaaS support behind the scenes. “In the private cloud, initial deployments were predominantly IaaS. Test and development types of cloud services were the first to be used in the enterprise; cloud was a radical change in deploying IT services, and this use was a safe and practical initial use of private cloud for enterprises. It was limited, and it did not pose a risk of disrupting the workings of IT resources in the enterprise. As trust in adoption of SaaS or mission-critical applications builds over time with technology enablement in processing power, storage advancements, memory advancements, and networking advancements, we foresee the adoption of SaaS type applications to accelerate over the forecast period, while shares of IaaS and PaaS workloads decline.”

On the consumer side, video and social networking will lead the increase in consumer workloads. By 2020, consumer cloud storage traffic per user will be 1.7 GB per month, compared to 513 MB per month in 2015. By 2020, video streaming workloads will account for 34% of total consumer workloads, compared to 29% in 2015. Social networking workloads will account for 24% of total consumer workloads, up from 20 percent in 2015. In the next four years, 59% (2.3 billion users) of the consumer Internet population will use personal cloud storage up from 47% (1.3 billion users) in 2015.

At the AWS re:Invent event, Amazon has announced a host of new services that highlight its commitment to enterprises. Andy Jassy, CEO of AWS, emphasized on the innovation in the areas of artificial intelligence, analytics, and hybrid cloud.

Amazon has been using deep learning and artificial intelligence in its retail business for enhancing the customer experience. The company claims that it has thousands of engineers working on artificial intelligence to improve search and discovery, fulfillment and logistics, product recommendations, and inventory management. Amazon is now bringing the same expertise to the cloud to expose the APIs that developers can consume to build intelligent applications. Dubbed as Amazon AI, the new service offers powerful AI capabilities such as image analysis, text to speech conversion, and natural language processing.

Amazon Rekognition is the rich image analysis service that can identify various attributes of an image. Amazon Polly is a service that accepts text or a string and returns an MP3 audio file containing the speech. With support for 47 different voices in 23 different languages, the service exposes rich cognitive speech capabilities. Amazon Lex is the new service for natural language processing and automatic speech recognition. It is the same service that powers Alexa and Amazon Echo. The service converts text or voice to a set of actions that developers can parse to perform a set of actions.

Amazon is also investing in MXNet, a deep learning framework that can run in a variety of environments. Apart from this, Amazon is also optimizing EC2 images to run popular deep learning frameworks including CNTK, TensorFlow, and Theano.

In the last decade, Amazon has added many services and features to its platform. While customers appreciate the pace of innovation, first-time users often complain about the overwhelming number of options and choices. Even to launch a simple virtual machine that runs a blog or a development environment in EC2, users may have to choose from a variety of options. To simplify the experience of launching non-mission critical workloads in EC2, AWS has announced a new service called Amazon Lightsail. Customers can launch a VM with just a few clicks without worrying about the complex choices that they need to make. When they get familiar with EC2, they can start integrating with other services such as EBS and Elastic IP. Starting at $5 a month, this is the cheapest compute service available in AWS. Amazon calls Lightsail as the express mode for EC2 as dramatically reduces the launch time of a VM.

Amazon Lightsail competes with the VPS providers such as DigitalOcean and Linode. The sweet spot of these vendors has been developers and non-technical users who need a virtual private server to run a workload in the cloud. With Amazon Lightsail, AWS wants to attract developers, small and medium businesses, and digital agencies that typically use a VPS service for their needs.

On the analytics front, Amazon is adding a new interactive, serverless query service called Amazon Athena that can be used to retrieve data stored in Amazon S3. The service supports complex SQL queries including joins to return data from Amazon S3. Customers can use custom metadata to perform complex queries. Amazon Athena’s pricing is based on per query model.

Last month, AWS and VMware partnered to bring hybrid cloud capabilities to customers. With this, customers can run and manage workloads in the cloud, seamlessly from existing VMware tools.

Amazon claims that the customers will be able to use VMware’s virtualization and management software to seamlessly deploy and manage VMware workloads across all of their on-premises and AWS environments. This offering allows customers to leverage their existing investments in VMware skills and tooling to take advantage of the flexibility of the AWS Cloud.

Pat Gelsinger, CEO of VMware was on stage with Andy Jassy talking about the value that this partnership brings to customers.

In a surprising move, Amazon is making its serverless computing framework, AWS Lambda available outside of its cloud environment. Extending Lambda to connected devices, AWS has announced AWS Greengrass – an embedded Lambda compute environment that can be installed in IoT devices and hubs. It delivers local compute, storage, and messaging infrastructure in environments that demand offline access. Developers can use the simple Lambda programming model to develop applications for both offline and online scenarios. Amazon Greengrass Core is designed to run on hub and gateways while Greengrass runtime will power low-end, resource-constrained devices.

Extending the hybrid scenarios to industrial IoT, Amazon has also announced a new appliance called Snowball Edge that runs Greengrass Core. This appliance is expected to be deployed in environments that generate extensive offline data. It exposes an S3-compatible endpoint for developers to use the same ingestion API as the cloud. Since the device runs Lambda, developers can create functions that respond to events locally. Amazon Snowball Edge ships with 100TB capacity, hi-speed Ethernet Wi-Fi, and 3G cellular connectivity. When the ingestion process is completed, customers can send the appliance to AWS for uploading the data.

Pushing the limits of data migration to the cloud, Amazon is also launching a specialized truck called AWS Snowmobile that can move Exabytes of data to AWS. The truck carries a 48-foot long container that can hold up to 100 Petabytes of data. Customers must call AWS to open the vestibule of the truck to start ingesting the data. They just need to plug the fiber cable and the power cable to start loading the data. Amazon estimates that the loading and unloading process takes about three months on each side.

Apart from these services, Andy Jassy has also announced a slew of enhancements to Amazon EC2 and RDS.

Over the last several years, stories of the technologies making up an Internet of Things have started to slip into public consciousness. As this is occurring, we believe the whole story of Smart Systems and the Internet of Things is not being told. Many of the dispatches coming in from the “front lines” of technology innovation are but fragments of a much larger narrative.

From our perspective, this story is not just about people communicating with people or machines communicating with machines. Smart, connected systems are a technological and economic phenomenon of unprecedented scale, encompassing potentially billions if not trillions of nodes — an Internet of infinite interactions and values…

During the past few years, much has been made of the billions of sensors, cameras, and other devices being connected exponentially in the “Internet of Things” (IoT)—and the trillions of dollars in potential economic value that is expected to come of it. Yet as exciting as the IoT future may be, a lot of the industry messaging has gone right over the heads of people who today operate plants, run businesses and are responsible for implementing IoT-based solutions. Investors find themselves wondering what is real, and what is a hyped-up vision of a future that is still years away.

Over the past decade, I have met with dozens of organizations in all corners of the globe, talking with people about IoT. I’ve worked with traditional industrial companies struggling to change outmoded manufacturing processes, and I’ve worked with innovative young startups that are redefining long-held assumptions and roles. And I can tell you that the benefits of IoT are not in some far-off future scenario. They are here and now—and growing. The question is not whether companies should begin deploying IoT—the benefits of IoT are clear—but how.

So, how do the companies get started on the IoT journey? It’s usually best to begin with a small, well-defined project that improves efficiency and productivity around existing processes. I’ve seen countless organizations, large and small, enjoy early success in their IoT journey by taking one of the following “fast paths” to IoT payback:

Connected operations. By connecting key processes and devices in their production process on a single network, iconic American motorcycle maker Harley Davidson increased productivity by 80%, reduced its build-to-order cycle from 18 months to two weeks, and grew overall profitability by 3%-4%.

Remote operations. A dairy company in India began remotely monitoring the freezers in its 150 ice cream stores, providing alerts in case of power outages. The company began realizing a payback within a month and saw a five-fold return on its investment within 13 months.

Predictive maintenance. Global mining company Rio Tinto uses sensors to monitor the condition of its vehicles, identifying maintenance needs before they become problems—and saves $2 million a day every time it avoids a breakdown.

These four well-proven scenarios are ideal candidates to get started on IoT projects. Armed with an early success, companies can then build momentum and begin to tackle more transformative IoT solutions. Here, IoT provides rich opportunities across many domains, including:

New business opportunities and revenue streams. Connected operations combined with 3D printing, for example, are making personalization and mass customization possible in ways not imagined a few years ago.

New business models. IoT enables equipment manufacturers to adopt service-oriented business models. By gathering data from devices installed at a customer site, manufacturers like Japanese industrial equipment maker Fanuc can offer remote monitoring, analytics and predictive maintenance services to reduce costs and improve uptime.

New business structures. In many traditional industries, customers have typically looked to a single vendor for a complete end-to-end solution, often using closed, proprietary technologies. Today IoT, with its flexibility, cost, and time-to-market advantages, is driving a shift to an open technology model where solution providers form an ecosystem of partners. As a result, each participant provides its best-in-class capabilities to contribute to a complete IoT solution for their customers.

New value propositions for consumers. IoT is helping companies provide new hyper-relevant customer experiences and faster, more accurate services than ever before. Just think of the ever-increasing volume of holiday gift orders placed online on “Black Monday.” IoT is speeding up the entire fulfillment process, from ordering to delivery. Connected robots and Radio Frequency Identification (RFIUD) tags in the warehouse make the picking and packing process faster and more accurate. Real-time preventive maintenance systems keep delivery vehicles up and running. Telematic sensors record temperate and humidity throughout the process. So, not only can you track your order to your doorstep, your packages are delivered on time—and they arrive in optimal condition.

So, yes, IoT is real today and is already having a tremendous impact. It is gaining traction in industrial segments, logistics, transportation, and smart cities. Other industries, such as healthcare, retail, and agriculture are following closely.

We are just beginning to understand IoT’s potential. But if you are an investor wondering where the smart money is going, one thing is certain: 10 years from now, you’ll have to look hard to find an industry that has not been transformed by IoT.

Allrecipes’ Alexa skill helps you cook, even if you’re not sure what you want to make.

Believe it or not, there hasn’t really been a comprehensive recipe skill for Amazon Echo speakers. Campbell’s skill is focused on the soup brand, IFTTT integration is imperfect and Jamie Oliver’s skill won’t read cooking instructions aloud. Allrecipes might just save the day, though. It just launched an Alexa skill that guides you through cooking 60,000 meals — and importantly, helps you find something to cook in the first place. You can ask what’s possible with the ingredients you have on hand, find a quick-to-make dish or check on measurements.

When you’re in the middle of cooking, you can pause, repeat or advance steps.

The skill is free to use, and works with any device that supports Alexa skills in the first place (including Fire TV). If it works as well as promised, it might be a crucial addition. The Echo is already the quintessential kitchen speaker for many people — it’s that much more useful if it can save you from flipping through a cookbook (or a recipe app on your phone) with your flour-covered hands.

Insights matter. Businesses that use artificial intelligence (AI), big data and the Internet of Things (IoT) technologies to uncover new business insights “will steal $1.2 trillion per annum from their less informed peers by 2020.” So says Forrester in a new report, “Predictions 2017: Artificial Intelligence Will Drive The Insights Revolution.”

Across all businesses, there will be a greater than 300% increase in investment in artificial intelligence in 2017 compared with 2016. Through the use of cognitive interfaces into complex systems, advanced analytics, and machine learning technology, AI will provide business users access to powerful insights never before available to them. It will help, says Forrester, “drive faster business decisions in marketing, ecommerce, product management and other areas of the business by helping close the gap from insights to action.”

The combination of AI, Big data, and IoT technologies will enable businesses investing in them and implementing them successfully to overcome barriers to data access and to mining useful insights. In 2017 these technologies will increase business’ access to data, broaden the types of data that can be analyzed, and raise the level of sophistication of the resulting insight. As a result, Forrester predicts an acceleration in the trend towards democratization of data analysis. While in 2015 it found that only 51% of data and analytics decision-makers said that they were able to easily obtain data and analyze it without the help of technologist, Forrester expects this figure to rise to around 66% in 2017.

Big data technologies will mature and vendors will increasingly integrate them with their traditional analytics platforms which will facilitate their incorporation in existing analytics processes in a wide range of organizations. The use of a single architecture for big data convergence with agile and actionable insights will become more widespread.

The third set of technologies supporting insight-driven businesses, those associated with IoT, will also become integrated with more traditional analytics offerings and Forrester expects the number of digital analytics vendors offering IoT insights capabilities to double in 2017. This will encourage their customers to invest in networking more devices and exploring the data they produce. For example, Forrester has found that 67% of telecommunications decision-makers are considering or prioritizing developing IoT or M2M initiatives in 2017.

The increased investment in IoT will lead to new type of analytics which in turn will lead to new business insights. Currently, much of the data that is generated by edge devices such as mobile phones, wearables, or cars, goes unused as “immature data and analytics practices cause most firms to squander these insights opportunities,” says Forrester. In 2016, less than 50% of data and analytics decision-makers have adopted location analytics, but Forrester expects the adoption of location analytics will grow to over two-thirds of businesses by the end of 2017. The resulting new insights will enable firms to optimize their customers’ experiences as they engage in the physical world with products, services and support.

In general, Forrester sees encouraging signs that more companies are investing in initiatives to get rid of existing silos of customer knowledge so they can coordinate better and drive insights throughout the entire enterprise. Specifically, Forrester sees three such initiatives becoming prominent in 2017:

Organizations with Chief Data Officers (CDOs) will become the majority in 2017, up from a global average of 47% in 2016. But to become truly insights-driven, says Forrester, “firms must eventually assign data responsibilities to CIOs and CMOs, and even CEOs, in order to drive swift business action based on data driven insights.”

Customer data management projects will increase by 75%. In 2016, for the first time, 39% of organizations have embarked on a big data initiative to support cross-channel tracking and attribution, customer journey analytics, and better segmentation. And nearly one-third indicated plans to adopt big data technologies and solutions in the next twelve months.

Forrester expects to see a marked increase in the adoption of enterprise-wide insights-driven practices as firms digitally transform their business in 2017. Leading customer intelligence practices and strategies will become “the poster child for business transformation,” says Forrester.

Want your IoT devices to last a billion years? Use an AA battery, or just suck the leakage out of your transistors, according to a new paper in the American Association for the Advancement of Science journal Science, published in the October 21 issue.

The two researchers, Sungsik Lee, Arokia Nathan, are both in the Electrical Engineering Division of the Engineering department of the University of Cambridge in the UK, have designed new ultralow power transistors that, if all goes as described, could function for years without a battery. They operate on ‘scavenged’ energy from their environment, and therefore should be able to power devices for months or years without a battery, and provide enough juice for wearable or implantable electronics.

It uses a principle similar to sleep mode, much like other low-power devices, but adds in the ability to harness electrical near-off-state current for its operations. This energy leakage is apparently common to all transistors, but this is the first time that it has been effectively captured and used functionally, the researchers said.

The transistors can be produced at low temperatures and can be printed on almost any material, from glass and plastic to polyester and paper. They are based on a unique geometry which uses a ‘non-desirable’ characteristic, namely the point of contact between the metal and semiconducting components of a transistor, or the ‘Schottky barrier.’

“We’re challenging conventional perception of how a transistor should be,” said Nathan. “We’ve found that these Schottky barriers, which most engineers try to avoid, actually have the ideal characteristics for the type of ultralow power applications we’re looking at, such as wearable or implantable electronics for health monitoring. This will bring about a new design model for ultralow power sensor interfaces and analogue signal processing in wearable and implantable devices, all of which are critical for the Internet of Things.”

The new design also addresses the issue of scale. As transistors get smaller, the electrodes will start to influence the behavior of one another and the voltages spread, so usually transistors fail to function below a certain size. With this design, the researchers were able to use the Schottky barriers to keep the electrodes independent from one another, so that the transistors can be scaled down to very small geometries.

The design also achieves a high level of gain, or signal amplification. The transistor’s operating voltage is less than a volt, with power consumption below a billionth of a watt.

“If we were to draw energy from a typical AA battery based on this design, it would last for a billion years,” said Lee. “Using the Schottky barrier allows us to keep the electrodes from interfering with each other in order to amplify the amplitude of the signal even at the state where the transistor is almost switched off.”

It was December 2008 and Twitter was barely two years old. At the time, many questioned the point of the 140-character messaging platform. Many still do.

But one doubting Thomas, stood out from the pack. Rather than just backstab the new social media tool in coffee shop conversations,Hans Scharler took action.

In a public demonstration highlighting the futility of Twitter, this American inventor and entrepreneur enabled his toaster to tweet.

You read right.

When Hans Scharler’s toaster is on, the @mytoaster Twitter handle tweets “Toasting.” When it’s done, it tweets “Done Toasting.” A small protest, yes. But a butterfly effect in the internet world. For it may have been this networked kitchen appliance, through it’s metaphorical wing flap, that created the hurricane of what is now called the “Internet of Things.”

And hurricane is no exaggeration. Today, the Internet of Things, or IoT, goes well beyond tweets regarding one’s breakfast status. In 2014, Google bought Nest, a home IoT collection of thermostats, smoke detectors, and other security systems, for an impressive $3.2 billion. That’s BILLION, with a “B.” And this storm is just growing. Research firm IDC believes that the global revenue for IoT will be $1.46 trillion by 2020. At that time it is estimated that somewhere between 25 to 200 billion devices will be connected within the IoT ecosystem.

“But hang on!” your internal monologue is screaming, “If IoT is this huge, why haven’t I heard of it before?”

Well, you have. The Internet of Things is sitting in your garage right now. Our cars, a “thing,” have been connected via the “internet” to other “things” for years now — although you took it all for granted. Jumping into the driver’s seat Monday morning, you overlooked the seamless link between your car stereo and smartphone.

On your journey to a client that same day, chances are you didn’t question the adjusted route based on real-time traffic alerts. And when you were headed home, and the car overheated, there’s a good chance that the requested emergency roadside assistance was triggered with a press of a button, or completely autonomously.

And that coffee you’re drinking? If you are sitting in Italy or Switzerland, then it may have been brought to you by IoT. Solair, an Italian company that was acquired this year by Microsoft for an undisclosed amount, has deployed its IoT cloud-based applications to help the Rancilio Group manage the coffee machines that it sells to hotels, restaurants and cafes. Through IoT, Rancilio manages coffee supplies, undertakes remote maintenance, and helps clients avoid sales losses through machine downtime. One hundred percent “thing”; zero percent human.

So where to next?

Well, globally there’s at least 88 publicly listed companies that are active in the IoT space. These companies include the obvious Cisco, Google, and IBM, but also lesser known firms like PTC, a company known for its design modelling software and product lifecycle management tools. PTC has also been snapping up smaller companies with existing capabilities within the Cloud service space and artificial intelligence (AI).

And it’s this trichotomy of IoT, Cloud and AI that allows for some very exciting products. TakeDRONEBOX, for example. Through IoT sensors, like the precision agriculture NDVI camera, crop harvests can be increased through better water and fertiliser management. And that’s just one application of the autonomous, self-charging drone.

IoT enabled thermal and high definition cameras expand the applications across asset inspection, emergency response, security, and even livestock management. And then there’s the myriad of other IoT sensors and actuators entering the market (see Figure 1, below). Once connected to the Cloud, these sensors open up a huge number of applications, as well a new field known as prescriptive analytics.

n short, prescriptive analytics combine hybrid data — a combination of structured (numbers, categories) and unstructured data (videos, images, sounds, texts) — with business rules to predict the future and to prescribe how to take advantage of this future scenario.

Hans Scharler’s IoT toaster, equipped with this computational power, would not only announce its current cooking status, but order the bread, jam and complementary orange juice in the previous week’s grocery order. It might also suggest a healthier option, based on a conversation it had with your IoT scales.

The malware that powered one of the worst denial of service cyberattacks of the last few years has infected internet-connected devices all over the world, reaching as many as 177 countries, according to security researchers.

Imperva, a company that provides protection to websites against Distributed Denial of Service (DDoS) attacks, is among the ones who have been busy investigating Mirai. According to their tally, the botnet made of Mirai-infected devices has reached a total of 164 countries. A pseudonymous researcher that goes by the name MalwareTechhas also been mapping Mirai, and according to his tally, the total is even higher, at 177 countries.

“Most indiscriminately spread malware will show up allover the globe,” MalwareTech said in a Twitter message.

Mirai was used to build a botnet that hit the website of security journalist Brian Krebs with a large DDoS attack last month. A hacker who goes by the name Anna-senpai released the source code of the malware at the beginning of October, but it’s unclear who really is behind it.

Mirai isn’t really a fancy piece of malware, but it’s effective and spreads quickly because it targets Internet of Things (IoT) devices that are extremely easy to hack. These devices, mostly DVRs and surveillance cameras, use default and predictable passwords, such as “admin” and “123456”, “root” and “password,” or “guest” and “guest,” among others.

Thanks to these bad passwords, and the Mirai malware, the Internet of (hackable) Things has truly gone global.

The ACMA’s new management plan will see it focus on incoming network technologies and the spectrum issues behind them, including mmW bands for 5G and spectrum sharing for IoT.

The Australian Communications and Media Authority (ACMA) has released its five-year spectrum outlook (FYSO) and 12-month work plan, with the federal government agency focusing on arrangements to support 5G, the Internet of Things (IoT), and dynamic spectrum access (DSA).

For 5G, the ACMA is considering the use of millimetre wave (mmW) bands.

“Enabling the next phase of mobile network development is likely to require the ACMA’s attention in a number of areas,” the FYSO said.

“From a spectrum perspective, 5G appears certain to use (though not exclusively) large contiguous bandwidths (hundreds of MHz or more) in millimetre wave bands.”

The ACMA is monitoring both high-frequency and low-frequency mmW bands, including the 2.3GHz, 2.5GHz, 3.5GHz, and 3.6GHz bands, for 5G mobile services.

“The 2.3GHz, 2.5GHz and 3.5GHz bands are already available for use for mobile broadband services in Australia and could feasibly be used for early deployment of 5G or pre-standard 5G in Australia,” the ACMA added.

“The 3.6GHz band is included in the initial investigation stage of ACMA’s mobile broadband work program.”

The ACMA is planning to publish a discussion paper on planning issues for the 1.5GHz and 3.6GHz spectrum bands over the next few weeks, with the latter band being eyed for 5G purposes worldwide.

For IoT concerns, the ACMA is looking at a broad range of spectrum bands due to the large number of varied uses and users involved.

“Given the huge diversity of uses of IoT, there is no simple solution to providing spectrum for all of the applications which are likely to require access to it under a range of protocols from dedicated spectrum to commons spectrum, and options in between,” ACMA acting chairman Richard Bean said at the CommsDay Congress in Melbourne this week.

“We are and have taken steps to make new spectrum available to support a range of low-power applications including M2M [machine-to-machine] applications in 900MHz band as part of the implementation of our review of the 803-960 band. Permanent arrangements in this band are not currently set to be in place until 2021, but we will consider early access applications.”

The ACMA is also examining IoT opportunities in the very high frequency (VHF) band.

The ACMA had previously argued in favour of a default spectrum band for all IoT devices across the globe, or, alternatively, sensors that can identify which country a device is operating in.

The government agency in December released a set of proposed changes to spectrum regulations aimed at providing easier access for M2M operators utilising spectrum for IoT, and outgoing ACMA chairman Chris Chapman in February emphasised the need for IoT spectrum.

In regards to DSA, the ACMA recognised spectrum sharing as being “fundamental” for efficient spectrum management. DSA relies on users and uses to co-exist on the same spectrum band, with awareness of the environment required.

The ACMA said there are currently three ways for devices to become more aware of their surroundings to enable dynamic sharing of a spectrum band.

“At this stage, three major techniques to enhance a device’s awareness of its surroundings have been identified: Geolocation with database look-up; sensing; and beacon transmissions,” the FYSO says.

“These techniques can be used to make use of spectrum ‘white space’, where secondary users take advantage of intermittent, occasional or itinerant use by primary users.”

The ACMA in July said spectrum sharing is the key to IoT and 5G, with ACMA Spectrum Planning Branch executive manager Christopher Hose saying that there needs to be more cooperation between industry and the ACMA to achieve this goal.

The agency said it recently implemented DSA across the 3400MHz-3600MHz spectrum band between Defence radar systems and terrestrial wireless broadband.

Lastly, the ACMA’s new 12-month work plan will see the agency focus on 10 projects across three “themes”. The first theme will see the ACMA implement its mobile broadband strategyby Q4 2016; work on priority compliance areas including interference management, customer cabling compliance, and transmitter licensing compliance across the 400MHz and by June 2017; set spectrum pricing initiatives by Q1 2017; look into spectrum allocations in the 700MHz, 850MHz, 1800MHz, 1.5GHz, 2GHz, 2.3GHz, 3.4GHz, and 3.6GHz bands; implement the regional digital radio rollout plan, with scoping to be completed by Q4 2016 and implementation from Q1 2017; and convert AM to FM commercial radio broadcasting services in selected regional licence areas between Q4 2016 and Q1 2017.

The second theme will see the ACMA develop its customer self-service program, with device registration and 900MHz station registration online forms made available in Q3 2016; XML payload form for APs to be made available in Q4 2016; and apparatus licence application forms to be available in Q1 2017.

The final theme will involve implementation of the government’s spectrum review in accordance with the Department of Communications’ timeline; implementation of the 400MHz spectrum band review, with the second milestone due between December 2016 and June 2017 and the third milestone in December 2017; and updating the Australian Radiofrequency Spectrum Plan in January 2017.

The ACMA is inviting comment on 5G mmW bands, IoT spectrum, DSA, and its approach to the new 12-month work plan in response to the FYSO.

When the website of security expert Brian Krebs recently went down, it wasn’t bad luck—it was the result of a huge surge of data: 620 gigabits per second. And now we know where it came from. It was an army of Internet-connected devices, being used as slaves to take down servers.

According to the Wall Street Journal, as many as one million security cameras, digital video recorders, and other connected devices have been employed by hackers to carry out a series of such attacks. When corralled together, these pieces of hardware can be used as a so-called botnet, collectively sending data and Web page requests to servers with such ferocity that they’re overwhelmed and ultimately crash.

It’s a powerful new way of putting an old idea into practice. Attackers have long installed malware on PCs to have them act as bots that they control, and more recently home routers and printers have been used to the same ends. But as Internet-connected devices proliferate in our homes and offices, the potential number of devices to draw upon is increasing dramatically.

The scale of the new set of attacks is unprecedented. According to the BBC, this recent spate has been able to barrage servers with data at rates of over a terabit per second. In addition to Krebs’s site, the targets have included the servers of French Web hosting provider OVH. The attacksmay have been carried out by the same botnet.

The news raises fresh concerns about the security of Internet of things devices. Purpose-built to be controlled over the Internet, such devices have been billed as the future of sensing and control to businesses and domestic users alike—from connected video cameras and speakers to smart thermostats and lightbulbs. While initially slow to gain popularity, they are proliferating as they’ve become increasingly user-friendly.

But there’s a problem. Many such devices are purchased, installed, and then used without much further attention being paid to their configuration. That means that they may never be updated, leaving huge scope for their exploitation by hackers if they contain a security flaw. (They invariably do.) Who, after all, bothers to update a lightbulb?

Earlier this year, the National Security Agency’s hacking chief, Rob Joyce, sounded caution over these kinds of devices. Their security is “something that keeps me up at night,” he said at the time.

For the IT sector, the concept of digital transformation represents a time for evolution, revolution and opportunity, according to Information Technology Association of Canada (ITAC) president Robert Watson.

The new president for the technology association made the statements at last week’s IDC Directions and CanadianCIO Symposium in Toronto. The tech trends event was co-hosted by ITWC and IDC with support from ITAC.

Digital transformation refers to the changes associated with the application of digital technology in all aspects of human society; the overarching event theme focused on digital transformation as more than mere buzzword, but as process that tech leaders and organizations should already be adopting. Considering the IT department is the “substance of every industry,” it follows that information technology can play a key role in setting the pace for innovation and future developments, offered Watson.

Both the public and private sectors are looking to diversify operations and economies — the IT sector will be the leaders and enable development of emerging technologies including the Internet of Things (IoT): “It is coming for sure and a fantastic opportunity.”

With that in mind, here are four key takeaways from the event.

“Have you ever seen a more dynamic, exciting, and scary time in our industry?”

IDC’s senior vice president and chief analyst Frank Gens outlined reasons why IT is currently entering an “innovation stage” with the era of the Third Platform, which refers to emerging tech such as cloud technology, mobile, social and IoT.

According to IDC, the Third Platform is anticipated to grow to approximately 20 per cent by the year 2020; eighty per cent of Fortune 100 companies are expected to have digital transformation teams in place by the end of this year.

“It’s about a new foundation for enterprise services. You can connect back-end AI to this growing edge of IoT…you are really talking about collective learning and accelerated learning around the next foundation of enterprise solutions,” said Gens.

Takeaway: In a cloud- and mobile-dominated IT world, enterprises should look to quickly develop platform- and API-based services across their network, noted Gens, while also looking to grow the developer base to use those services.

“Robotics is an extremely vertical driven solution.”

Think of that classic 1927 film Metropolis, and its anthropomorphic robot Maria: While IT has come a long way from Metropolis in terms of developments in robotics, the industry isn’t quite there yet. But we’re close, noted IDC research analyst Vlad Mukherjee, and the industry should look at current advancements in the field.

According to Mukherjee, robotics are driving digital transformation processes by establishing new revenue streams and changing the way we work.

Currently, robotics tech is classified in terms of commercial service, industry and consumer. Canadian firms in total are currently spending $1.08 B on the technology, Mukherjee said.

Early adopters are looking at reducing costs; this includes the automotive and manufacturing sectors, but also fields such as healthcare, logistics, and resource extraction. In the case of commercial service robotics, the concept works and the business case is there, but not at the point where we can truly take advantage, he said.

The biggest expense for robotics is service, maintenance, and battery life, said Mukherjee.

Takeaway: Industrial robots are evolving to become more flexible, easier to setup, support more human interaction and be more autonomously mobile. Enterprises should keep abreast of robotics developments, particularly the rise of collaborative industrial robots which have a lower barrier for SME adoption. This includes considering pilot programs and use cases that explore how the technology can help improve operations and automated processes.

“China has innovated significantly in terms of business models that the West has yet to emulate.”

Analysts Bryan Ma, vice-president of client devices for IDC Asia-Pacific, and Krista Collins, research manager of mobility and consumer for IDC Canada, outlined mobility trends and why the mobility and augmented or virtual reality markets seen in the east will inevitably make their way to Canada.

China is no longer considered a land of cheap knockoffs, said Ma, adding consider the rise of companies like Xiaomi, considered “The Apple of China.”

Globally, shipments of virtual reality (VR) hardware are expected to skyrocket this year, according to IDC’s forecasts. It expects shipments to hit 9.6 million units worldwide, generating $2.3 billion mostly for the four lead manufacturers: Samsung, Sony, HTC, and Oculus.

With VR in its early days, both Ma and Collins see the most growth potential for the emerging medium coming from the consumer market. Gaming and even adult entertainment options promise to be the first use-cases for mass adoption, with applications in the hospitality, real estate, or travel sectors coming later.

“That will be bigger on the consumer side of the market,” Collins said. “That’s what we’ll see first here in Canada and in other parts of the world.”

Takeaway: Augmented reality (AR) headsets will take longer to ramp up, IDC expects. In 2016, less than half a million units will ship. That will quickly climb to 45.6 million units by 2020, chasing the almost 65 million expected shipments of VR headsets. But unlike VR, the first applications for AR will be in the business world.

“Technology is integrated with everything”

There are currently more than 3.8 billion mobile phones on the planet — just think of the opportunities, offered David Senf, vice president of infrastructure solutions for IDC Canada.

He argued that digital transformation is an even bigger consideration than security — and responding to business concerns is a top concern for IT in 2016. IT staff spent two weeks more “keeping the lights on” in 2015 versus being focused on new, innovative projects. This has to change, said Senf.

IT is living in an era of big data and advanced analytics. As cloud technology matures — from just being software-as-a-service (SaaS) to platform-as-a-service (PaaS) and infrastructure-as-a-service (IaaS) — CIOs should think about the cloud in a new way. Instead of just the cloud, it’s a vital architecture that should be supporting the business.

“Organizations are starting to define what that architecture looks like,” said Senf, adding the successful ones understand that the cloud is a competitive driver, particularly from an identity management, cost, and data residency perspective.

Takeaway: If the infrastructure isn’t already ready for big data, it might already be behind the curve. Senf notes CIOs should ensure that the IT department is able to scale quickly for change — and is ready to support the growing demands of the business side, including mobility public cloud access.

Get ready to experiment and become comfortable with data sources and analysis. This includes looking at the nature of probabilistic findings — and using PaaS, he added.

When we started this decade, the Internet of Things was a basically a buzzword, talked about by a few, acted upon by fewer, a challenge to save for the future, like 2015 or 2020.

But as a famous character once said in a movie that’s now 30 years old, “life moves pretty fast…” and now, here we are with 2015 in the rear view mirror and our 2020 vision becoming clearer by the minute.

Everyone’s talking about the Internet of Things, even the “things,” which can now request and deliver customer support, tell if you’re being as productive as you could be at work, let your doctor know if you’re following orders (or not), reduce inefficiencies in energy consumption, improve business processes, predict issues and proactively improve or resolve them based on data received.

The Internet of Things (IoT) is just getting started. These forecasts below show why organizations need to get started too (if they haven’t already) on leveraging and responding to the Internet of Things:

5. In a 2016 PwC survey of 1,000 U.S. consumers, 45% say they now own a fitness band, 27% a smartwatch, and 12% smart clothing. 57% say they are excited about the future of wearable technology as part of everyday life. 80% say wearable devices make them more efficient at home, 78% more efficient at work. – PwC The Wearable Life 2.0: Connected Living in a Wearable World

7. 65% of approximately 1,000 global business executives surveyed say they agree organizations that leverage the internet of things will have a significant advantage; 19% however, still say they have never heard of the Internet of Things. – Internet of Things Institute 2016 I0T Trends Survey

12. Barcelona estimates that IoT systems have helped the city save $58 million a year from connected water management and $37 million a year via smart street lighting alone. – Harvard University Report

13. General Electric estimates that the “Industrial Internet” market (connected industrial machinery) will add $10 to $15 trillion to the global GDP within the next 20 years. – GE Reports

14. General Electric believes that using connected industrial machinery to make oil and gas exploration and development just 1% more efficient would result in a savings of $90 billion. – GE Reports

The Internet of Things is accelerating the transformation of the way we live and work. Life move pretty fast. Stop and look around, but don’t miss it. Is your organization leveraging the Internet of Things?